Welcome to Data retriever’s documentation!

Contents:

User Guide

We handle the data so you can focus on the science

Finding data is one thing. Getting it ready for analysis is another. Acquiring, cleaning, standardizing and importing publicly available data is time consuming because many datasets lack machine readable metadata and do not conform to established data structures and formats.

The Data Retriever automates the first steps in the data analysis pipeline by downloading, cleaning, and standardizing datasets, and importing them into relational databases, flat files, or programming languages. The automation of this process reduces the time for a user to get most large datasets up and running by hours, and in some cases days.

What data tasks does the Retriever handle

The Data Retriever handles a number of common tasks including:

1. Creating the underlying database structures, including automatically determining the data types
2. Downloading the data
3. Transforming data into appropriately normalized forms for database management systems (e.g., “wide” data into “long” data and splitting tables into proper sub-tables to reduce duplication)
4. Converting heterogeneous null values (e.g., 999.0, -999, NaN) into standard null values
5. Combining multiple data files into single tables; and 6) placing all related tables in a single database or schema.

A couple of examples on the more complicated end include the Breeding Bird Survey of North America (breed-bird-survey) and the Alwyn Gentry Tree Transect data(gentry-forest-transects):

• Breeding bird survey data consists of multiple tables. The main table is divided into one file per region in 70 individual compressed files. Supplemental tables required to work with the data are posted in a variety of locations and formats. The Data Retriever automates: downloading all data files, extracting data from region-specific raw data files into single tables, correcting typographic errors, replacing non-standard null values, and adding a Species table that links numeric identifiers to actual species names.
• The Gentry forest transects data is stored in over 200 Excel spreadsheets, each representing an individual study site, and compressed in a zip archive. Each spreadsheet contains counts of individuals found at a given site and all stems measured from that individual; each stem measurement is placed in a separate column, resulting in variable numbers of columns across rows, a format that is difficult to work with in both database and analysis software. There is no information on the site in the data files themselves, it is only present in the names of the files. The Retriever downloads the archive, extracts the files, and splits the data they contain into four tables: Sites, Species, Stems, and Counts, keeping track of which file each row of count data originated from in the Counts table and placing a single stem on each row in the Stems table.

Adapted from Morris & White 2013.

Installing (binaries)

Precompiled binaries of the most recent release are available for Windows, OS X, and Ubuntu/Debian at the project website.

Installing From Source

Required packages

To install the Data Retriever from source, you’ll need Python 3.6.8+ with the following packages installed:

• xlrd

The following packages are optional

• PyMySQL (for MySQL)
• sqlite3 (for SQLite, v3.8 or higher required)
• psycopg2-binary (for PostgreSQL)
• pypyodbc (for MS Access)

Steps to install from source

1. Clone the repository
2. From the directory containing setup.py, run the following command: python setup.py install or use pip pip install . --upgrade to install and pip uninstall retriever to uninstall the retriever
3. After installing, type retriever from a command prompt to see the available options of the Data Retriever. Use retriever --version to confirm the version installed on your system.

Using the Data Retriever Commands

After installing, run retriever update to download all of the available dataset scripts. Run retriever ls to see the available datasets

To see the full list of command line options and datasets run retriever --help. The output will look like this:

usage: retriever [-h] [-v] [-q]
                 {download,install,defaults,update,new,new_json,edit_json,delete_json,ls,citation,reset,help,commit}
                 ...

positional arguments:
  {download,install,defaults,update,new,new_json,edit_json,delete_json,ls,citation,reset,help}
                        sub-command help
    download            download raw data files for a dataset
    install             download and install dataset
    defaults            displays default options
    update              download updated versions of scripts
    new                 create a new sample retriever script
    new_json            CLI to create retriever datapackage.json script
    edit_json           CLI to edit retriever datapackage.json script
    delete_json         CLI to remove retriever datapackage.json script
    ls                  display a list all available dataset scripts
    citation            view citation
    reset               reset retriever: removes configuration settings,
                        scripts, and cached data
    help
    commit              commit dataset to a zipped file
    log                 see log of a committed dataset

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -q, --quiet           suppress command-line output

To install datasets, use the install command.

Examples

Using install

The install command downloads the datasets and installs them in the desired engine.

$ retriever install -h (gives install options)

usage: retriever install [-h] [--compile] [--debug]
                         {mysql,postgres,sqlite,msaccess,csv,json,xml} ...
positional arguments:
  {mysql,postgres,sqlite,msaccess,csv,json,xml}
                        engine-specific help
    mysql               MySQL
    postgres            PostgreSQL
    sqlite              SQLite
    msaccess            Microsoft Access
    csv                 CSV
    json                JSON
    xml                 XML
optional arguments:
  -h, --help            show this help message and exit
  --compile             force re-compile of script before downloading
  --debug               run in debug mode

Examples using install

These examples use Breeding Bird Survey data (breed-bird-survey). The retriever has support for various databases and flat file formats (mysql, postgres, sqlite, msaccess, csv, json, xml). All the engines have a variety of options or flags. Run `retriever defaults to see the defaults. For example, the default options for mysql and postgres engines are given below.

retriever defaults

Default options for engine  MySQL
user   root
password
host   localhost
port   3306
database_name   {db}
table_name   {db}.{table}

Default options for engine  PostgreSQL
user   postgres
password
host   localhost
port   5432
database   postgres
database_name   {db}
table_name   {db}.{table}

Help information for a particular engine can be obtained by running retriever install [engine name] [-h] [–help], for example, retriever install mysql -h. Both mysql and postgres require the database user name --user [USER], -u [USER] and password --password [PASSWORD], -p [PASSWORD]. MySQL and PostgreSQL database management systems support the use of configuration files. The configuration files provide a mechanism to support using the engines without providing authentication directly. To set up the configuration files please refer to the respective database management systems documentation.

Install data into Mysql:

retriever install mysql –-user myusername –-password ***** –-host localhost –-port 8888 –-database_name testdbase breed-bird-survey
retriever install mysql –-user myusername breed-bird-survey (using attributes in the client authentication configuration file)

Install data into postgres:

retriever install postgres –-user myusername –-password ***** –-host localhost –-port 5432 –-database_name testdbase breed-bird-survey
retriever install postgres breed-bird-survey (using attributes in the client authentication configuration file)

Install data into sqlite:

retriever install sqlite breed-bird-survey -f mydatabase.db (will use mydatabase.db)
retriever install sqlite breed-bird-survey (will use or create default sqlite.db in working directory)

Install data into csv:

retriever install csv breed-bird-survey --table_name  "BBS_{table}.csv"
retriever install csv breed-bird-survey

Using download

The download command downloads the raw data files exactly as they occur at the source without any clean up or modification. By default the files will be stored in the working directory.

--path can be used to specify a location other than the working directory to download the files to. E.g., --path ./data

--subdir can be used to maintain any subdirectory structure that is present in the files being downloaded.

retriever download -h (gives you help options)
retriever download breed-bird-survey (download raw data files to the working directory)
retriever download breed-bird-survey –path  C:\Users\Documents (download raw data files to path)

Using citation

The citation command show the citation for the retriever and for the scripts.

retriever citation (citation of the Data retriever)
retriever citation breed-bird-survey (citation of Breed bird survey data)

To create new, edit, delete scripts please read the documentation on scripts

Storing database connection details

The retriever reads from the standard configuration files for the database management systems. If you want to store connection details they should be stored in those files. Make sure to secure these files appropriately.

For postgreSQL, create or modify ~/.pgpass. This is a file named .pgpass located in the users home directory. On Microsoft Windows, the file is named %APPDATA%postgresqlpgpass.conf (where %APPDATA% refers to the Application Data subdirectory in the user’s profile). It should take the general form:

hostname:port:database:username:password

where each word is replaced with the correct information for your database connection or replaced with an * to apply to all values for that section.

For MySQL, create or modify ~/.my.cnf. This is a file named .my.cnf located in the users home directory. The relevant portion of this file for the retriever is the client section which should take the general form:

[client]
host=hostname
port=port
user=username
password=password

where each word to the right of the = is replaced with the correct information for your database connection. Remove or comment out the lines for any values you don’t want to set.

Acknowledgments

Development of this software was funded by the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative through Grant GBMF4563 to Ethan White and the National Science Foundation as part of a CAREER award to Ethan White.

Quick Start

The Data Retriever is written in Python and has a Python interface, a command line interface or an associated R package. It installs publicly available data into a variety of databases (MySQL, PostgreSQL, SQLite) and flat file formats (csv, json, xml).

Installation

Using conda:

$ conda install retriever -c conda-forge

or pip:

$ pip install retriever

To install the associated R package:

$ install.packages('rdataretriever')

Python interface

Import:

$ import retriever as rt

List available datasets:

$ rt.dataset_names()

Load data on GDP from the World bank:

$ rt.fetch('gdp')

Install the World Bank data on GDP into an SQLite databased named “gdp.sqlite”:

$ rt.install_sqlite('gdp', file='gdp.sqlite)

Command line interface

List available datasets:

$ retriever ls

Install the Portal dataset into a set of json files:

$ retriever install json portal

Install the Portal dataset into an SQLite database named “portal.sqlite”:

$ retriever install sqlite portal -f portal.sqlite

R interface

List available datasets:

$ rdataretriever::datasets()

Load data on GDP from the World bank:

$ rdataretriever::fetch(dataset = 'gdp')

Install the GDP dataset into SQLite:

$ rdataretriever::install('gdp', 'sqlite')

Learn more

Check out the rest of the documentation for more commands, details, and datasets.

Available install formats for all interfaces are: mysql, postgres, sqlite, csv, json, and xml.

Using the Data Retriever from R

rdataretriever

The rdataretriever provides an R interface to the Data Retriever so that the retriever’s data handling can easily be integrated into R workflows.

Installation

To use the R package rdataretriever, you first need to install the Data Retriever.

The rdataretriever can then be installed using install.packages("rdataretriever")

To install the development version, use devtools

# install.packages("devtools")
library(devtools)
install_github("ropensci/rdataretriever")

Note: The R package takes advantage of the Data Retriever’s command line interface, which must be available in the path. This path is given to the rdataretriever using the function use_RetrieverPath(). The location of retriever is dependent on the Python installation (Python.exe, Anaconda, Miniconda), the operating system and the presence of virtual environments in the system. The following instances exemplify this reliance and how to find retriever’s path.

Ubuntu OS with default Python:

If retriever is installed in default Python, it can be found out in the system with the help of which command in the terminal. For example:

$ which retriever
/home/<system_name>/.local/bin/retriever

The path to be given as input to use_RetrieverPath() function is /home/<system_name>/.local/bin/ as shown below:

library(rdataretriever)
use_RetrieverPath("/home/<system_name>/.local/bin/")

The which command in the terminal finds the location of retriever including the name of the program, but the path required by the function is the directory that contains retriever. Therefore, the retriever needs to be removed from the path before using it.

Ubuntu OS with Anaconda environment:

When retriever is installed in an virtual environment, the user can track its location only when that particular environment is activated. To illustrate, assume the virtual environment is py27:

$ conda activate py27
(py27) $ which retriever
/home/<system_name>/anaconda2/envs/py27/bin/retriever

This path can be used for rdataretriever after removing retriever as follows:

library(rdataretriever)
use_RetrieverPath("/home/<system_name>/anaconda2/envs/py27/bin/")

Note: rdataretriever will be able to locate retriever even if the virtual environment is deactivated.

rdataretriever functions:

datasets()

Description : The function returns a list of available datasets.

Arguments : No arguments needed.

Example :

rdataretriever::datasets()

fetch()

Description : Each datafile in a given dataset is downloaded to a temporary directory and then imported as a data.frame as a member of a named list.

Arguments :

• dataset (String): Name of dataset to be downloaded
• quiet (Bool): The argument decides if warnings need to be displayed (TRUE/FALSE)
• data_name (String): Name assigned to dataset once it is downloaded

Example :

rdataretriever :: fetch(dataset = 'portal')

download()

Description : Used to download datasets directly without cleaning them and when user does not have a specific preference for the format of the data and the kind of database.

Arguments :

• dataset (String): Name of the dataset to be downloaded.
• path (String): Specify dataset download path.
• quiet (Bool): Setting TRUE minimizes the console output.
• sub_dir (String): sub_dir downloaded dataset is stored into a custom subdirectory.
• debug (Bool): Setting TRUE helps in debugging in case of errors.
• use_cache (Bool): Setting FALSE reinstalls scripts even if they are already installed.

Example :

rdataretriever :: download("iris","/Users/username/Desktop")

Installation functions

Format specific installation

Description : rdataretriever supports installation of datasets in three file formats through different functions:

• csv (install_csv)
• json (install_json)
• xml (install_xml)

Arguments : These functions require same arguments.

• dataset (String): Name of the dataset to install.
• table_name (String): Specify the table name to install.
• data_dir (String): Specify the dir path to store data, defaults to working dir
• debug (Bool): Setting TRUE helps in debugging in case of errors.
• use_cache (Bool): Setting FALSE reinstalls scripts even if they are already installed.

Example :

rdataretriever :: install_csv("bird-size",table_name = "Bird_Size",debug = TRUE)

Database specific installation

Description : rdataretriever supports installation of datasets in four different databses through different functions:

• MySQL (install_mysql)
• PostgreSQL (install_postgres)
• SQLite (install_sqlite)
• MSAccess (install_msaccess)

Arguments for PostgreSQL and MySQL :

• database_name (String): Specify database name.
• debug (Bool): Setting True helps in debugging in case of errors.
• host (String): Specify host name for database.
• password (String): Specify password for database.
• port (Int): Specify the port number for installation.
• quiet (Bool): Setting True minimizes the console output.
• table_name (String): Specify the table name to install.
• use_cache (Bool): Setting False reinstalls scripts even if they are already installed.
• user (String): Specify the username.

Example :

rdataretriever :: install_postgres(dataset = 'portal', user='postgres', password='abcdef')

Arguments for MSAccess and SQLite :

• file (String): Enter file_name for database.
• table_name (String): Specify the table name to install.
• debug (Bool): Setting True helps in debugging in case of errors.
• use_cache (Bool): Setting False reinstalls scripts even if they are already installed.

Example :

rdataretriever :: install_sqlite(dataset = 'iris', file = 'sqlite.db',debug=FALSE, use_cache=TRUE)

get_updates()

Description : This function will check if the version of the retriever’s scripts in your local directory ‘ ~/.retriever/scripts/’ is up-to-date with the most recent official retriever release.

Example :

rdataretriever :: get_updates()

reset()

Description : The function will Reset the components of rdataretriever using scope [ all, scripts, data, connection]

Arguments :

• scope : Specifies what components to reset. Options include: ’scripts’, ’data’, ’connection’ and ’all’, where ’all’ is the default setting that resets all components.

Example :

rdataretriever :: reset(scope = 'data')

Examples

library(rdataretriever)

# List the datasets available via the retriever
rdataretriever::datasets()

# Install the Gentry forest transects dataset into csv files in your working directory
rdataretriever::install('gentry-forest-transects', 'csv')

# Download the raw Gentry dataset files without any processing to the
# subdirectory named data
rdataretriever::download('gentry-forest-transects', './data/')

# Install and load a dataset as a list
Gentry = rdataretriever::fetch('gentry-forest-transects')
names(gentry-forest-transects)
head(gentry-forest-transects$counts)

To get citation information for the rdataretriever in R use citation(package = 'rdataretriever'):

Using the retriever-recipes

retriever-recipes

The Data Retriever earlier used a simple CLI for developing new dataset scripts. This allowed users with no programming experience to quickly add most standard datasets to the Retriever by specifying the names and locations of the tables along with additional information about the configuration of the data. The script is saved as a JSON file, that follows the DataPackage standards.

This functionality has been moved to the retriever-recipes repository to separate the scripts from the core retriever functionalities to help with organization, maintenance, and testing. The retriever recipes repository thus holds all the scripts which were earlier shipped with retriever and also all the script adding/editing functionalities.

Installation

The retriever-recipes project can be installed from Github using the following steps:

git clone https://www.github.com/weecology/retriever-recipes.git
cd retriever-recipes
python setup.py install

Script Creation

To create a new script, there are 2 methods :-

1. Use retriever autocreate to automatically create a script template. Specify the type of data using -dt, the default data type is tabular. Download the files to a folder. In case of tabular data, the files should be CSV files. Autocreate can create a script template for each file using -f or use -d to create a single script template for all files in the directory.

usage: retriever autocreate [-h] [-dt [{raster,vector,tabular}]] [-f] [-d]
                            [-o [O]] [--skip-lines SKIP_LINES]
                            path

positional arguments:
  path                  path to the data file(s)

optional arguments:
  -h, --help            show this help message and exit
  -dt [{raster,vector,tabular}]
                        datatype for files
  -f                    turn files into scripts
  -d                    turn a directory and subdirectories into scripts
  -o [O]                write scripts out to a designated directory
  --skip-lines SKIP_LINES
                        skip a set number of lines before processing data

2. Manual script creation using retriever-recipes new_json, which starts the CLI tool for new script creation.

Required

1. name: A one word name for the dataset

Strongly recommended

1. title: Give the name of the dataset
2. description: A brief description of the dataset of ~25 words.
3. citation: Give a citation if available
4. homepage: A reference to the data or the home page
5. keywords: Helps in classifying the type of data (i.e using Taxon, Data Type, Spatial Scale, etc.)

Mandatory for any table added; Add Table? (y/N)

1. table-name: Name of the table, URL to the table
2. table-url: Name of the table, URL to the table

Basic Scripts

The most basic scripts structure requires only some general metadata about the dataset, i.e., the shortname of the database and table, and the location of the table.

Example of a basic script, example.script

Creating script from the CLI

name (a short unique identifier; only lowercase letters and - allowed): example-mammal
title: Mammal Life History Database - Ernest, et al., 2003
description:
citation: S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.
homepage (for the entire dataset):
keywords (separated by ';'): mammals ; compilation

Add Table? (y/N): y
table-name: species
table-url: http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt
missing values (separated by ';'):
replace_columns (separated by ';'):
delimiter:
do_not_bulk_insert (bool = True/False):
contains_pk (bool = True/False):
escape_single_quotes (bool = True/False):
escape_double_quotes (bool = True/False):
fixed_width (bool = True/False):
header_rows (int):
Enter columns [format = name, type, (optional) size]:


Add crosstab columns? (y,N): n

Add Table? (y/N): n

Created script

{
    "citation": "S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.",
    "description": "",
    "homepage": "",
    "keywords": [
        "Mammals",
        "Compilation"
    ],
    "name": "example-mammal",
    "resources": [
        {
            "dialect": {},
            "name": "species",
            "schema": {
                "fields": []
            },
            "url": "http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt"
        }
    ],
    "retriever": "True",
    "retriever_minimum_version": "2.0.dev",
    "title": "Mammal Life History Database - Ernest, et al., 2003"
    "version": "1.0.0"
}

Explanation for the keys:

• citation: Citation for the dataset
• description: Description for the dataset
• homepage: Homepage or website where the data is hosted
• keywords: Keywords/tags for the dataset (for searching and classification)
• name: Shortname for the dataset. Unique, URL-identifiable
• resources: List of tables within the dataset
  • dialect: Metadata for retriever to process the table
    • missingValues: (Optional) List of strings which represents missing values in tables
    • delimiter: (Optional) a character which represent boundary between two separate value(ex. ‘,’ in csv files)
    • header_rows: (Optional) number of header rows in table.
  • name: Name of the table
  • schema: List of the columns in the table
    • fields: (Optional-Recommended) List of columns and their types and (optional) size values
    • ct_column: (Optional) Cross-tab column with column names from dataset
  • url: URL of the table
• retriever: Auto generated tag for script identification
• retriever_minimum_version: Minimum version that supports this script
• title: Title/Name of the dataset
• urls: dictionary of table names and the respective urls
• version: “1.0.0”

Multiple Tables

A good example of data with multiple tables is Ecological Archives E091-124-D1, McGlinn et al. 2010. plant-comp-ok Vascular plant composition data. Since there are several csv files, we create a table for each of the files.

Assuming we want to call our dataset McGlinn2010, below is an example of the script that will handle this data

...
  "name": "McGlinn2010",
  "resources": [
      {
          "dialect": {},
          "name": "pres",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_pres.csv"
      },
      {
          "dialect": {},
          "name": "cover",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_cover.csv"
      },
      {
          "dialect": {},
          "name": "richness",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_rich.csv"
      },
      {
          "dialect": {},
          "name": "species",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_specodes.csv"
      },
      {
          "dialect": {},
          "name": "environment",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_env.csv"
      },
      {
          "dialect": {},
          "name": "climate",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E091/124/TGPP_clim.csv"
      }
  ],
  "retriever": "True",
  "retriever_minimum_version": "2.0.dev",
  "title": "Vascular plant composition - McGlinn, et al., 2010",
  ...

Null Values

The Retriever can replace non-standard null values by providing a semi-colon separated list of those null values after the table in which the null values occur.

...
Table name: species
Table URL: http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt
nulls (separated by ';'): -999 ; 'NA'
...

For example, the Adler et al. 2010. mapped-plant-quads-ks script uses -9999 to indicate null values.

...
      {
          "dialect": {},
          "name": "quadrat_info",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/quadrat_info.csv"
      },
      {
          "dialect": {
              "missingValues": [
                  "NA"
              ]
          },
...

Headers

If the first row of a table is the headers then naming the columns will, be default, be handled automatically. If you want to rename an existing header row for some reason, e.g., it includes reserved keywords for a database management system, you can do so by adding a list of semi-colon separated column names, with the new columns provided after a comma for each such column.

...
Add Table? (y/N): y
Table name: species
Table URL: http://esapubs.org/archive/ecol/E091/124/TGPP_specodes.csv
replace_columns (separated by ';', with comma-separated values): jan, january ; feb, february ; mar, march
...

The mapped-plant-quads-ks script for the Adler et al. 2007. dataset from Ecological Archives includes this functionality:

...
 "name": "mapped-plant-quads-ks",
  "resources": [
      {
          "dialect": {},
          "name": "main",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/allrecords.csv"
      },
      {
          "dialect": {},
          "name": "quadrat_info",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/quadrat_info.csv"
      },
      {
          "dialect": {
              "missingValues": [
                  "NA"
              ]
          },
          "name": "quadrat_inventory",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/quadrat_inventory.csv"
      },
      {
          "dialect": {},
          "name": "species",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/species_list.csv"
      },
      {
          "dialect": {
              "missingValues": [
                  "NA"
              ],
              "replace_columns": [
                  [
                      "jan",
                      "january"
                  ],
                  [
                      "feb",
                      "february"
                  ],
                  [
                      "mar",
                      "march"
                  ],
                  [
                      "apr",
                      "april"
                  ],
                  [
                      "jun",
                      "june"
                  ],
                  [
                      "jul",
                      "july"
                  ],
                  [
                      "aug",
                      "august"
                  ],
                  [
                      "sep",
                      "september"
                  ],
                  [
                      "oct",
                      "october"
                  ],
                  [
                      "nov",
                      "november"
                  ],
                  [
                      "dec",
                      "december"
                  ]
              ]
          },
          "name": "monthly_temp",
          "schema": {},
          "url": "http://esapubs.org/archive/ecol/E088/161/monthly_temp.csv"
      },
  ...

Data Format

Data packages for different data formats can been added to Retriever now. To add data format add keys in the script for Data sources except in the case of csv.

Data formats which can be added are :-

1. JSON Data :- For JSON raw data, add the key word json_data to the resource. To add data formats for a given data package(nuclear-power-plants), add keys to the resource part as described below.

...
 "name": "nuclear-power-plants",
  "resources": [
      {
          "dialect": {
              "delimiter": ","
          },
          "name": "nuclear_power_plants",
          "path": "nuclear_power_plants.csv",
          "json_data": "nuclear_power_plants.json",
          "schema": {
              "fields": [
                  {
                      "name": "id",
                      "type": "int"
                  },
                  {
                      "name": "name",
                      "size": "40",
                      "type": "char"
                  },
  ...

2. XML Data :- For XML raw data, add the key words xml_data and empty_rows to the resource. To add data formats for a given data package(county-emergency-management-offices), add keys to the resource part as described below.

...
"name": "county-emergency-management-offices",
  "resources": [
      {
          "dialect": {
              "delimiter": ","
          },
          "name": "county_emergency_management_offices",
          "path": "County_Emergency_Management_Offices.csv",
          "xml_data": "emergency_offices.xml",
          "empty_rows": 1,
          "schema": {
              "fields": [
                  {
                      "name": "county",
                      "size": "11",
                      "type": "char"
                  },
                  {
                      "name": "emergency_manager",
                      "size": "20",
                      "type": "char"
  ...

3. SQlite Data :- For SQlite raw data, add the key word sqlite_data to the resource. To add data formats for a given data package(portal-project-test), add keys to the resource part as described below.

...
 "name": "portal-project-test",
  "resources": [
      {
          "dialect": {
              "delimiter": ","
          },
          "name": "species",
          "path": "species.csv",
          "sqlite_data": ["species","portal_project.sqlite"],
          "schema": {
              "fields": [
                  {
                      "name": "species_id",
                      "size": "2",
                      "type": "char"
                  },
                  {
                      "name": "genus",
                      "size": "16",
                      "type": "char"
                  },
  ...

4. GeoJSON Data :- For GeoJSON raw data, add the key word geojson_data to the resource. To add data formats for a given data package(lake-county-illinois-cancer-rates), add keys to the resource part as described below.

...
 "name": "lake-county-illinois-cancer-rates",
  "resources": [
      {
          "dialect": {
              "delimiter": ","
          },
          "name": "lakecounty_health",
          "path": "LakeCounty_Health.csv",
          "format": "tabular",
          "geojson_data": "mytest.geojson",
          "schema": {
              "fields": [
                  {
                      "name": "fid",
                      "type": "int"
                  },
                  {
                      "name": "zip",
                      "type": "int"
                  },

  ...

5. HDF5 Data :- For HDF5 raw data, add the key word hdf5_data to the resource. To add data formats for a given data package(sample-hdf), add keys to the resource part as described below.

...
 "name": "sample-hdf",
"title": "Test data raster bio1",
"description": "Test data sampled from bioclim bio1",
"citation": "N/A",
"keywords": [
  "tests"
],
"encoding": "latin-1",
"url": "https://github.com/ashishpriyadarshiCIC/My_data/raw/main/Test_table_image_data.h5",
"ref": "N/A",
"version": "1.0.0",
"retriever_minimum_version": "2.1.dev",
"driver": "GTiff",
"colums": 284,
"rows": 249,
"band_count": 1,
"datum": "N/A - Coordinate Reference System",
"projection": "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.0174532925199433],AUTHORITY[\"EPSG\",\"4326\"]]",
"file_size": "N/A",
"group_count": "N/A",
"dataset_count": "N/A",
"transform": {
  "xOrigin": -121.6250000000029,
  "pixelWidth": 0.041666666666667,
  "rotation_2": 0.0,
  "yOrigin": 42.79166666666632,
  "rotation_4": 0.0,
  "pixelHeight": -0.041666666666667
},
"resources": [
  {
    "dialect": {
      "delimiter": ","
    },
    "name": "table_data",
    "path": "table_data.csv",
    "hdf5_data": [
      "Test_table_image_data.h5",
      "csv",
      "G1/table_data"
    ],
    "schema": {
      "fields": [
        {
          "name": "region",
          "size": "33",
          "type": "char"
        },
        {
          "name": "country",
          "size": "32",
          "type": "char"
        },
        {
          "name": "item_type",
          "size": "15",
          "type": "char"
        },
        {
          "name": "sales_channel",
          "size": "7",
          "type": "char"
        },
        {
          "name": "order_id",
          "type": "int"
        },
        {
          "name": "total_profit",
          "type": "double"
        }
      ]
    },
    "url": "https://github.com/ashishpriyadarshiCIC/My_data/raw/main/Test_table_image_data.h5"
  },
  {
    "name": "test_image",
    "format": "raster",
    "hdf5_data": [
      "Test_table_image_data.h5",
      "image",
      "G1/G2/im"
    ],
    "path": "test_raster_bio1.tif",
    "extensions": [
      "tif"
    ],
    "no_data_value": -9999.0,
    "min": null,
    "max": null,
    "scale": 1.0,
    "color_table": null,
    "statistics": {
      "minimum": 0.0,
      "maximum": 0.0,
      "mean": 0.0,
      "stddev": -1.0
    },
  ...

Full control over column names and data types

By default the Retriever automatically detects both column names and data types, but you can also exercise complete control over the structure of the resulting database by adding column names and types.

It is recommended to describe the schema of the table while creating the JSON file. This enables processing of the data faster since column detection increases the processing time.

These values are stored in the fields array of the schema dict of the JSON script.

The fields value enables full control of the columns, which includes, renaming columns, skipping unwanted columns, mentioning primary key and combining columns.

The basic format for fields is as shown below:

...
Enter columns [format = name, type, (optional) size]:

count, int
name, char, 40
year, int
...

where name represents name of the column and type represents the type of data present in the column. The following can be used to describe the data type:

pk-auto: Auto generated primary key starting from 1
pk-[char,int,double]: primary key with data type
char: strings
int: integers
double:floats/decimals
ct-[int,double,char]:Cross tab data
skip: used to skip the column in database

pk-auto is used to create an additional column of type int which acts as a primary key with values starting from 1. While pk-[char,int,double] is used to make a primary key from existing columns of the table having data type of char/int/double.

The Smith et al. Masses of Mammals mammal-masses dataset script includes this type of functionality.

...
   "name": "mammal-masses",
  "resources": [
      {
          "dialect": {
              "missingValues": [
                  -999
              ],
              "header_rows": 0
          },
          "name": "MammalMasses",
          "schema": {
              "fields": [
                  {
                      "name": "record_id",
                      "type": "pk-auto"
                  },
                  {
                      "name": "continent",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "status",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "sporder",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "family",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "genus",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "species",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "log_mass_g",
                      "type": "double"
                  },
                  {
                      "name": "comb_mass_g",
                      "type": "double"
                  },
                  {
                      "name": "reference",
                      "type": "char"
                  }
              ]
          },
          "url": "http://www.esapubs.org/Archive/ecol/E084/094/MOMv3.3.txt"
      }
  ],
  "retriever": "True",
  "retriever_minimum_version": "2.0.dev",
  "title": "Masses of Mammals (Smith et al. 2003)",
...

Restructuring cross-tab data

It is common in ecology to see data where the rows indicate one level of grouping (e.g., by site), the columns indicate another level of grouping (e.g., by species), and the values in each cell indicate the value for the group indicated by the row and column (e.g., the abundance of species x at site y). This is referred as cross-tab data and cannot be easily handled by database management systems, which are based on a one record per line structure. The Retriever can restructure this type of data into the appropriate form. In scripts this involves telling the retriever the name of the column to store the data in and the names of the columns to be restructured.

...
Add crosstab columns? (y,N): y
Crosstab column name: <name of column to store cross-tab data>
Enter names of crosstab column values (Press return after each name):

ct column 1
ct column 2
ct column 3
...

The Moral et al 2010 script. mt-st-helens-veg takes advantage of this functionality.

...
"name": "mt-st-helens-veg",
  "resources": [
      {
          "dialect": {
              "delimiter": ","
          },
          "name": "species_plot_year",
          "schema": {
              "ct_column": "species",
              "ct_names": [
                  "Abilas",
                  "Abipro",
                  "Achmil",
                  "Achocc",
                  "Agoaur",
                  "Agrexa",
                  "Agrpal",
                  "Agrsca",
                  "Alnvir",
                  "Anamar",
                  "Antmic",
                  "Antros",
                  "Aqifor",
                  "Arcnev",
                  "Arnlat",
                  "Astled",
                  "Athdis",
                  "Blespi",
                  "Brocar",
                  "Brosit",
                  "Carmer",
                  "Carmic",
                  "Carpac",
                  "Carpay",
                  "Carpha",
                  "Carros",
                  "Carspe",
                  "Casmin",
                  "Chaang",
                  "Cirarv",
                  "Cisumb",
                  "Crycas",
                  "Danint",
                  "Descae",
                  "Elyely",
                  "Epiana",
                  "Eriova",
                  "Eripyr",
                  "Fesocc",
                  "Fravir",
                  "Gencal",
                  "Hiealb",
                  "Hiegra",
                  "Hyprad",
                  "Junmer",
                  "Junpar",
                  "Juncom",
                  "Leppun",
                  "Lommar",
                  "Luepec",
                  "Luihyp",
                  "Luplat",
                  "Luplep",
                  "Luzpar",
                  "Maiste",
                  "Pencar",
                  "Pencon",
                  "Penser",
                  "Phahas",
                  "Phlalp",
                  "Phldif",
                  "Phyemp",
                  "Pincon",
                  "Poasec",
                  "Poldav",
                  "Polmin",
                  "Pollon",
                  "Poljun",
                  "Popbal",
                  "Potarg",
                  "Psemen",
                  "Raccan",
                  "Rumace",
                  "Salsit",
                  "Saxfer",
                  "Senspp",
                  "Sibpro",
                  "Sorsit",
                  "Spiden",
                  "Trispi",
                  "Tsumer",
                  "Vacmem",
                  "Vervir",
                  "Vioadu",
                  "Xerten"
              ],
              "fields": [
                  {
                      "name": "record_id",
                      "type": "pk-auto"
                  },
                  {
                      "name": "plot_id_year",
                      "size": "20",
                      "type": "char"
                  },
                  {
                      "name": "plot_name",
                      "size": "4",
                      "type": "char"
                  },
                  {
                      "name": "plot_number",
                      "type": "int"
                  },
                  {
                      "name": "year",
                      "type": "int"
                  },
                  {
                      "name": "count",
                      "type": "ct-double"
                  }
              ]
          },
          "url": "http://esapubs.org/archive/ecol/E091/152/MSH_SPECIES_PLOT_YEAR.csv"
      },
...

Script Editing

Note: Any time a script gets updated, the minor version number must be incremented from within the script.

The JSON scripts created using the retriever-recipes CLI can also be edited using the CLI.

To edit a script, use the retriever-recipes edit_json command, followed by the script’s shortname;

For example, editing the mammal-life-hist (Mammal Life History Database - Ernest, et al., 2003) dataset, the editing tool will ask a series a questions for each of the keys and values of the script, and act according to the input.

The tool describes the values you want to edit. In the script below the first keyword is citation, citation ( <class 'str'> ) and it is of class string or expects a string.

dev@retriever:~$ retriever-recipes edit_json mammal-life-hist

  ->citation ( <class 'str'> ) :

  S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402

  Select one of the following for the key 'citation'

  1. Modify value
  2. Remove from script
  3. Continue (no changes)


  Your choice: 3

    ->homepage ( <class 'str'> ) :

    http://esapubs.org/archive/ecol/E084/093/


  Select one of the following for the key 'homepage':

  1. Modify value
  2. Remove from script
  3. Continue (no changes)


  Your choice: 3

    ->description ( <class 'str'> ) :

    The purpose of this data set was to compile general life history characteristics for a variety of mammalian
    species to perform comparative life history analyses among different taxa and different body size groups.


  Select one of the following for the key 'description':

  1. Modify value
  2. Remove from script
  3. Continue (no changes)


  Your choice: 3

    ->retriever_minimum_version ( <class 'str'> ) :

    2.0.dev


  Select one of the following for the key 'retriever_minimum_version':

  1. Modify value
  2. Remove from script
  3. Continue (no changes)


  Your choice: 3

    ->version ( <class 'str'> ) :

    1.1.0


  Select one of the following for the key 'version':

  1. Modify value
  2. Remove from script
  3. Continue (no changes)


  Your choice: 3

    ->resources ( <class 'list'> ) :

    {'dialect': {}, 'schema': {}, 'name': 'species', 'url': 'http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt'}


  1 .  {'dialect': {}, 'schema': {}, 'name': 'species', 'url': 'http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt'}

  Edit this dict in 'resources'? (y/N): n
  Select one of the following for the key 'resources':

  1. Add an item
  2. Delete an item
  3. Remove from script
  4. Continue (no changes)
  ...

Data Retriever using Python

Data Retriever is written purely in python. The Python interface provides the core functionality supported by the CLI (Command Line Interface).

Installation

The installation instructions for the CLI and module are the same. Links have been provided below for convenience.

• Instructions for installing from binaries project website.
• Instructions for installing from source install from Source.

Note: The python interface requires version 2.1 and above.

Tutorial

Importing retriever

>>> import retriever

In this tutorial, the module will be referred to as rt.

>>> import retriever as rt

List Datasets

Listing available datasets using dataset_names function. The function returns a list of all the currently available scripts.

>>> rt.dataset_names()

['abalone-age',
 'antarctic-breed-bird',
 .
 .
 'wine-composition',
 'wine-quality']

For a more detailed description of the scripts installed in retriever, the datasets function can be used. This function returns a list of Scripts objects. From these objects, we can access the available Script’s attributes as follows.

>>> for dataset in rt.datasets():
      print(dataset.name)

abalone-age
airports
amniote-life-hist
antarctic-breed-bird
aquatic-animal-excretion
.
.

There are a lot of different attributes provided in the Scripts class. Some notably useful ones are:

- name
- citation
- description
- keywords
- title
- urls
- version

You can add more datasets locally by yourself. Adding dataset documentation.

Update Datasets

If there are no scripts available, or you want to update scripts to the latest version, check_for_updates will download the most recent version of all scripts.

>>> rt.check_for_updates()

Downloading scripts...
Download Progress: [####################] 100.00%
The retriever is up-to-date

Downloading recipes for all datasets can take a while depending on the internet connection.

Download Datasets

To directly download datasets without cleaning them use the download function

def download(dataset, path='./', quiet=False, subdir=False, debug=False):

A simple download for the iris dataset can be done using the following.

>>> rt.download("iris")

Output:

=> Downloading iris

Downloading bezdekIris.data...
100%  0 seconds Copying bezdekIris.data

The files will be downloaded into your current working directory by default. You can change the default download location by using the path parameter. Here, we are downloading the NPN dataset to our Desktop directory

>>> rt.download("NPN","/Users/username/Desktop")

Output:

=> Downloading NPN

Downloading 2009-01-01.xml...
11  MBB
Downloading 2009-04-02.xml...
42  MBB
.
.

path (String): Specify dataset download path.

quiet  (Bool): Setting True minimizes the console output.

subdir (Bool): Setting True keeps the subdirectories for archived files.

debug  (Bool): Setting True helps in debugging in case of errors.

Install Datasets

Retriever supports installation of datasets into 7 major databases and file formats.

- csv
- json
- msaccess
- mysql
- postgres
- sqlite
- xml

There are separate functions for installing into each of the 7 backends:

def install_csv(dataset, table_name=None, compile=False, debug=False,
            quiet=False, use_cache=True):

def install_json(dataset, table_name=None, compile=False,
             debug=False, quiet=False, use_cache=True, pretty=False):

def install_msaccess(dataset, file=None, table_name=None,
                 compile=False, debug=False, quiet=False, use_cache=True):

def install_mysql(dataset, user='root', password='', host='localhost',
              port=3306, database_name=None, table_name=None,
              compile=False, debug=False, quiet=False, use_cache=True):

def install_postgres(dataset, user='postgres', password='',
                 host='localhost', port=5432, database='postgres',
                 database_name=None, table_name=None,
                 compile=False, debug=False, quiet=False, use_cache=True):

def install_sqlite(dataset, file=None, table_name=None,
               compile=False, debug=False, quiet=False, use_cache=True):

def install_xml(dataset, table_name=None, compile=False, debug=False,
            quiet=False, use_cache=True):

A description of default parameters mentioned above:

compile         (Bool): Setting True recompiles scripts upon installation.

database_name (String): Specify database name. For postgres, mysql users.

debug           (Bool): Setting True helps in debugging in case of errors.

file          (String): Enter file_name for database. For msaccess, sqlite users.

host          (String): Specify host name for database. For postgres, mysql users.

password      (String): Specify password for database. For postgres, mysql users.

port             (Int): Specify the port number for installation. For postgres, mysql users.

pretty          (Bool): Setting True adds indentation in JSON files.

quiet           (Bool): Setting True minimizes the console output.

table_name    (String): Specify the table name to install.

use_cache       (Bool): Setting False reinstalls scripts even if they are already installed.

user          (String): Specify the username. For postgres, mysql users.

Examples to Installing Datasets:

Here, we are installing the dataset wine-composition as a CSV file in our current working directory.

rt.install_csv("wine-composition")

=> Installing wine-composition

Downloading wine.data...
100%  0 seconds Progress: 178/178 rows inserted into ./wine_composition_WineComposition.csv totaling 178

The installed file is called wine_composition_WineComposition.csv

Similarly, we can download any available dataset as a JSON file:

rt.install_json("wine-composition")

=> Installing wine-composition

Progress: 178/178 rows inserted into ./wine_composition_WineComposition.json totaling 17

The wine-composition dataset is now installed as a JSON file called wine_composition_WineComposition.json in our current working directory.

Retriever Provenance

Retriever allows committing of datasets and installation of the committed dataset into the database of your choice at a later date. This ensures that the previous outputs/results can be produced easily.

Provenance Directory

The directory to save your committed dataset can be defined by setting the environment variable PROVENANCE_DIR. However, you can still save the committed dataset in a directory of your choice by defining the path while committing the dataset.

Commit Datasets

Retriever supports committing of a dataset into a compressed archive.

def commit(dataset, commit_message='', path=None, quiet=False):

A description of the default parameters mentioned above:

dataset               (String): Name of the dataset.

commit_message        (String): Specify commit message for a commit.

path                  (String): Specify the directory path to store the compressed archive file.

quiet                   (Bool): Setting True minimizes the console output.

Example to commit dataset:

retriever commit abalone-age -m "Example commit" --path .
Committing dataset abalone-age
Successfully committed.

>>> from retriever import commit
>>> commit('abalone-age', commit_message='Example commit', path='/home/')

If the path is not provided the committed dataset is saved in the provenance directory.

Log Of Committed Datasets

You can view the log of commits of the datasets stored in the provenance directory.

def commit_log(dataset):

A description of the parameter mentioned above:

dataset       (String): Name of the dataset.

Example:

retriever log abalone-age

Commit message: Example commit
Hash: 02ee77
Date: 08/16/2019, 16:12:28

>>> from retriever import commit_log
>>> commit_log('abalone-age')

Installing Committed Dataset

You can install committed datasets by using the hash-value or by providing the path of the compressed archive. Installation using hash-value is supported only for datasets stored in the provenance directory.

For installing dataset from a committed archive you can provide the path to the archive in place of dataset name:

retriever install sqlite abalone-age-02ee77.zip

>>> from retriever import install_sqlite
>>> install_sqlite('abalone-age-02ee77.zip')

Also, you can install using the hash-value of the datasets stored in provenance directory. You can always look up the hash-value of your previous commits using the command retriever log dataset_name.

For installing dataset from provenance directory provide the hash-value of the commit.

retriever install sqlite abalone-age --hash-value 02ee77

>>> from retriever import install_sqlite
>>> install_sqlite('abalone-age', hash_value='02ee77')

Datasets Available

1. Nesting ecology and offspring recruitment in a long-lived turtle

name:turtle-offspring-nesting reference:https://figshare.com/articles/Data_Paper_Data_Paper/3531323 citation:Lisa E. Schwanz, Rachel M. Bowden, Ricky-John Spencer, and Fredric J. Janzen. 2009. Nesting ecology and offspring recruitment in a long-lived turtle. Ecology 90:1709. [https://doi.org/10.6084/m9.figshare.3531323.v1] description:Valuable empirical resource for exploring important facets of nesting ecology and hatchling recruitment in a wild population of a long-lived species.

2. BioTIME species identities and abundances

name:biotime reference:https://zenodo.org/record/1095628#.WskN7dPwYyn citation:Dornelas M, Antão LH, Moyes F, et al. BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology & Biogeography. 2018; 00:1 - 26. https://doi.org/10.1111/geb.12729. description:The BioTIME database has species identities and abundances in ecological assemblages through time.

3. The effects of biodiversity on ecosystem community, and population variables reported 1974-2004

name:biodiversity-response reference:https://figshare.com/articles/Data_Paper_Data_Paper/3530822 citation:Bernhard Schmid, Andrea B. Pfisterer, and Patricia Balvanera. 2009. Effects of biodiversity on ecosystem community, and population variables reported 1974-2004. Ecology 90:853 description:

4. Croche understory vegetation data set

name:croche-vegetation-data reference:https://figshare.com/articles/Data_Paper_Data_Paper/3528707 citation:Alain Paquette, Etienne Laliberté, André Bouchard, Sylvie de Blois, Pierre Legendre, and Jacques Brisson. 2007. Lac Croche understory vegetation data set (1998-2006). Ecology 88:3209. description:The Lac Croche data set covers a nine-year period (1998-2006) of detailed understory vegetation sampling of a temperate North American forest located in the Station de Biologie des Laurentides (SBL), Québec, Canada.

5. ND-Gain

name:nd-gain reference:http://index.gain.org/ citation:Chen, C., Noble, I., Hellmann, J., Coffee, J., Murillo, M. and Chawla, N., 2015. University of Notre Dame Global Adaptation Index Country Index Technical Report. ND-GAIN: South Bend, IN, USA. description:The ND-GAIN Country Index summarizes a country’s vulnerability to climate change and other global challenges in combination with its readiness to improve resilience. It aims to help governments, businesses and communities better prioritize investments for a more efficient response to the immediate global challenges ahead.

6. Biomass and Its Allocation in Chinese Forest Ecosystems (Luo, et al., 2014)

name:forest-biomass-china reference:forest-biomass-china’s home link. citation:Yunjian Luo, Xiaoquan Zhang, Xiaoke Wang, and Fei Lu. 2014. Biomass and its allocation in Chinese forest ecosystems. Ecology 95:2026. description:Forest biomass data set of China which includes tree overstory components (stems, branches, leaves, and roots, among all other plant material), the understory vegetation (saplings, shrubs, herbs, and mosses), woody liana vegetation, and the necromass components of dead organic matter (litterfall, suspended branches, and dead trees).

7. The ph_ownership_history dataset

name:harvard-forest reference:http://harvardforest.fas.harvard.edu/ citation:Hall B. 2017. Historical GIS Data for Harvard Forest Properties from 1908 to Present. Harvard Forest Data Archive: HF110. description:ph_ownership_history

8. Mammal Community DataBase (Thibault et al. 2011)

name:mammal-community-db reference:https://figshare.com/articles/Data_Paper_Data_Paper/3552243 citation:Katherine M. Thibault, Sarah R. Supp, Mikaelle Giffin, Ethan P. White, and S. K. Morgan Ernest. 2011. Species composition and abundance of mammalian communities. Ecology 92:2316. description:This data set includes species lists for 1000 mammal communities, excluding bats, with species-level abundances available for 940 of these communities.

9. Wisconsin Breast Cancer Database

name:breast-cancer-wi reference:http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29 citation:Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. description:Database containing information on Wisconsin Breast Cancer Diagnostics

10. MammalDIET

name:mammal-diet reference:Not available citation:Kissling WD, Dalby L, Flojgaard C, Lenoir J, Sandel B, Sandom C, Trojelsgaard K, Svenning J-C (2014) Establishing macroecological trait datasets:digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide. Ecology and Evolution, online in advance of print. doi:10.1002/ece3.1136 description:MammalDIET provides a comprehensive, unique and freely available dataset on diet preferences for all terrestrial mammals worldwide.

11. Bioclim 2.5 Minute Climate Data

name:bioclim reference:http://worldclim.org/bioclim citation:Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. description:Bioclimatic variables that are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables.

12. Ecoregions of the Conterminous United States

name:ecoregions-us reference:ecoregions-us’s home link. citation:[‘U.S. Environmental Protection Agency. 2011. Level III ecoregions of the conterminous United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000’, ‘U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the conterminous United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon.’] description:Ecoregions of the Conterminous United States

13. Mapeamento de iniciativas (e catálogos) de dados abertos governamentais no Brasil.

name:catalogos-dados-brasil reference:https://github.com/dadosgovbr/catalogos-dados-brasil citation:Augusto Herrmann, Catálogos de dados abertos no Brasil, (2015), https://github.com/dadosgovbr/catalogos-dados-brasil description:Um catálogo de dados é uma coleção curada de metadados a respeito de conjuntos de dados

14. Global Biotic Interactions (GloBI) data

name:globi-interaction reference:https://github.com/jhpoelen/eol-globi-data/wiki citation:Poelen, J.H., Simons, J.D. and Mungall, C.J., 2014. Global biotic interactions: an open infrastructure to share and analyze species-interaction datasets. Ecological Informatics, 24, pp.148-159. description:GloBI contains code to normalize and integrate existing species-interaction datasets and export the resulting integrated interaction dataset.

15. GDP Data

name:gdp reference:https://github.com/datasets/gdp/blob/master citation:NA description:Country, regional and world GDP in current US Dollars ($). Regional means collections of countries e.g. Europe & Central Asia. Data is sourced from the World Bank and turned into a standard normalized CSV.

16. 3-D maps of tree canopy geometries at leaf scale

name:tree-canopy-geometries reference:https://figshare.com/articles/Data_Paper_Data_Paper/3530507 citation:Hervé Sinoquet, Sylvain Pincebourde, Boris Adam, Nicolas Donès, Jessada Phattaralerphong, Didier Combes, Stéphane Ploquin, Krissada Sangsing, Poonpipope Kasemsap, Sornprach Thanisawanyangkura, Géraldine Groussier-Bout, and Jérôme Casas. 2009. 3-D maps of tree canopy geometries at leaf scale. Ecology 90:283 description:This data set reports the three-dimensional geometry of a set of fruit and rubber trees at the leaf scale

17. Percentage leaf herbivory across vascular plant species

name:leaf-herbivory reference:leaf-herbivory’s home link. citation:Martin M. Turcotte, Christina J. M. Thomsen, Geoffrey T. Broadhead, Paul V. A. Fine, Ryan M. Godfrey, Greg P. A. Lamarre, Sebastian T. Meyer, Lora A. Richards, and Marc T. J. Johnson. 2014. Percentage leaf herbivory across vascular plant species. Ecology 95:788. http://dx.doi.org/10.1890/13-1741.1. description:Spatially explicit measurements of population level leaf herbivory on 1145 species of vascular plants from 189 studies from across the globe.

18. Abalone Age and Size Data

name:abalone-age reference:http://archive.ics.uci.edu/ml/datasets/Abalone citation:Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. description:Database to aid in the prediction of the age of an Abalone given physical measurements

19. Effects of biodiversity on the functioning of ecosystems:A summary of 164 experimental manipulations of species richness

name:species-exctinction-rates reference:https://figshare.com/articles/Data_Paper_Data_Paper/3530825 citation:Bradley J. Cardinale, Diane S. Srivastava, J. Emmett Duffy, Justin P. Wright, Amy L. Downing, Mahesh Sankaran, Claire Jouseau, Marc W. Cadotte, Ian T. Carroll, Jerome J. Weis, Andy Hector, and Michel Loreau. 2009. Effects of biodiversity on the functioning of ecosystems:A summary of 164 experimental manipulations of species richness. Ecology 90:854. description:A summary of the results on the accelerating rates of species extinction

20. Mapped plant quadrat time-series from Kansas (Adler et al. 2007)

name:mapped-plant-quads-ks reference:https://figshare.com/articles/Data_Paper_Data_Paper/3528368 citation:Peter B. Adler, William R. Tyburczy, and William K. Lauenroth. 2007. Long-term mapped quadrats from Kansas prairie:demographic information for herbaceaous plants. Ecology 88:2673. description:Demographic data for testing current theories in plant ecology and forecasting the effects of global change.

21. Poker Hand dataset

name:poker-hands reference:http://archive.ics.uci.edu/ml/datasets/Poker+Hand citation:Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. description:A dataset used to predict poker hands

22. Long term limnological measures in Acton Lake, database, 1992-2017

name:acton-lake reference:acton-lake’s home link. citation:Michael J Vanni, Maria J Gonzalez, and William H Renwick. 2019. Long term limnological measures in Acton Lake, a southwest Ohio reservoir, and its inflow streams: 1992-2017. Environmental Data Initiative. description:Long-term data collected from Acton Lake and its inflow streams, on a suite of physical, chemical and biological variables investigating how Acton Lake, responds to changes in ecosystem subsidies of detritus (sediments) and nutrients.

23. Portal Project Data (Ernest et al. 2009)

name:

portal

reference:

https://figshare.com/articles/Data_Paper_Data_Paper/3531317

citation:

19. 11. Morgan Ernest, Thomas J. Valone, and James H. Brown. 2009. Long-term monitoring and experimental manipulation of a Chihuahuan Desert ecosystem near Portal, Arizona, USA. Ecology 90:1708.

description:

The data set represents a Desert ecosystems using the composition and abundances of ants, plants, and rodents has occurred continuously on 24 plots. Currently includes only mammal data.

24. Bird Body Size and Life History (Lislevand et al. 2007)

name:bird-size reference:https://figshare.com/articles/Data_Paper_Data_Paper/3527864 citation:Terje Lislevand, Jordi Figuerola, and Tamas Szekely. 2007. Avian body sizes in relation to fecundity, mating system, display behavior, and resource sharing. Ecology 88:1605. description:A comprehensive compilation of data set on avian body sizes that would be useful for future comparative studies of avian biology.

25. Mount St. Helens vegetation recovery plots (del Moral 2010)

name:mt-st-helens-veg reference:mt-st-helens-veg’s home link. citation:Roger del Moral. 2010. Thirty years of permanent vegetation plots, Mount St. Helens, Washington. Ecology 91:2185. description:Documenting vegetation recovery from volcanic disturbances using the most common species found in non-forested habitats on Mount St. Helens.

26. First-flowering dates of plants in the Northern Great Plains

name:ngreatplains-flowering-dates reference:https://figshare.com/articles/Data_Paper_Data_Paper/3531716 citation:Steven E. Travers and Kelsey L. Dunnell. 2009. First-flowering dates of plants in the Northern Great Plains. Ecology 90:2332. description:Observations data of first-flowering time of native and nonnative plant species in North Dakota and Minnesota over the course of 51 years in the last century

27. Wine Quality

name:

wine-quality

reference:

wine-quality’s home link.

citation:

16. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis.

description:

Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests

28. A stream gage database for evaluating natural and altered flow conditions in the conterminous United States.

name:streamflow-conditions reference:https://figshare.com/articles/Data_Paper_Data_Paper/3544358 citation:James A. Falcone, Daren M. Carlisle, David M. Wolock, and Michael R. Meador. 2010. GAGES:A stream gage database for evaluating natural and altered flow conditions in the conterminous United States. Ecology 91:621. description:streamflow in ecosystems

29. The data was used to investigate patterns and causes of variation in NPP by the giant kelp, Macrocystis pyrifera, which is believed to be one of the fastest growing autotrophs on earth.

name:macrocystis-variation reference:https://figshare.com/articles/Data_Paper_Data_Paper/3529700 citation:Andrew Rassweiler, Katie K. Arkema, Daniel C. Reed, Richard C. Zimmerman, and Mark A. Brzezinski. 2008. Net primary production, growth, and standing crop of Macrocystis pyrifera in southern California. Ecology 89:2068. description:

30. Phylogeny and metabolic rates in mammals (Ecological Archives 2010)

name:mammal-metabolic-rate reference:https://figshare.com/collections/Phylogeny_and_metabolic_scaling_in_mammals/3303477 citation:Isabella Capellini, Chris Venditti, and Robert A. Barton. 2010. Phylogeny and metabolic rates in mammals. Ecology 20:2783-2793. description:Data on basal metabolic rate (BMR) with experimental animal body mass, field metabolic rate (FMR) with wild animal body mass, and sources of the data. Ecological Archives E091-198-S1.

31. National_Lakes_Assessment_Data

name:nla reference:nla’s home link. citation:NA description:The National Aquatic Resource Surveys (NARS) are statistical surveys designed to assess the status of and changes in quality of the coastal waters of the nation, lakes and reservoirs, rivers and streams, and wetlands. Using sample sites selected at random, these surveys provide a snapshot of the overall condition of water belonging to the nation. Because the surveys use standardized field and lab methods, we can compare results from different parts of the country and between years. EPA works with state, tribal and federal partners to design and implement the National Aquatic Resource Surveys.

32. Sagebrush steppe mapped plant quadrats (Zachmann et al. 2010)

name:mapped-plant-quads-id reference:https://figshare.com/articles/Data_Paper_Data_Paper/3550215 citation:Luke Zachmann, Corey Moffet, and Peter Adler. 2010. Mapped quadrats in sagebrush steppe:long-term data for analyzing demographic rates and plant-plant interactions. Ecology 91:3427. description:This data set consists of 26 permanent 1-m2 quadrats located on sagebrush steppe in eastern Idaho, USA.

33. Oosting Natural Area (North Carolina) plant occurrence (Palmer et al. 2007)

name:plant-occur-oosting reference:https://figshare.com/articles/Data_Paper_Data_Paper/3528371 citation:Michael W. Palmer, Robert K. Peet, Rebecca A. Reed, Weimin Xi, and Peter S. White. 2007. A multiscale study of vascular plants in a North Carolina Piedmont forest. Ecology 88:2674. description:A data set collected in 1989 of vascular plant occurrences in overlapping grids of nested plots in the Oosting Natural Area of the Duke Forest, Orange County, North Carolina, USA.

34. A database on visible diurnal spring migration of birds

name:bird-migration-data reference:https://figshare.com/articles/Data_Paper_Data_Paper/3551952 citation:Georg F. J. Armbruster, Manuel Schweizer, and Deborah R. Vogt. 2011. A database on visible diurnal spring migration of birds (Central Europe:Lake Constance). Ecology 92:1865. description:Birds migration data

35. Antarctic Site Inventory breeding bird survey data, 1994-2013

name:antarctic-breed-bird reference:antarctic-breed-bird’s home link. citation:Heather J. Lynch, Ron Naveen, and Paula Casanovas. 2013. Antarctic Site Inventory breeding bird survey data, 1994-2013. Ecology 94:2653. description:The data set represents the accumulation of 19 years of seabird population abundance data which was collected by the Antarctic Site Inventory, an opportunistic vessel-based monitoring program surveying the Antarctic Peninsula and associated sub-Antarctic Islands.

36. Dataset containing information on all airports on ouraiports.com

name:airports reference:http://ourairports.com/data/ citation:OurAirports.com, Megginson Technologies Ltd. description:Dataset containing information on all airports on ourairports.com

37. Body sizes of consumers and their resources

name:predator-prey-body-ratio reference:https://figshare.com/articles/Data_Paper_Data_Paper/3525119 citation:Ulrich Brose, Lara Cushing, Eric L. Berlow, Tomas Jonsson, Carolin Banasek-Richter, Louis-Felix Bersier, Julia L. Blanchard, Thomas Brey, Stephen R. Carpenter, Marie-France Cattin Blandenier, Joel E. Cohen, Hassan Ali Dawah, Tony Dell, Francois Edwards, Sarah Harper-Smith, Ute Jacob, Roland A. Knapp, Mark E. Ledger, Jane Memmott, Katja Mintenbeck, John K. Pinnegar, Bjorn C. Rall, Tom Rayner, Liliane Ruess, Werner Ulrich, Philip Warren, Rich J. Williams, Guy Woodward, Peter Yodzis, and Neo D. Martinez10. 2005. Body sizes of consumers and their resources. Ecology 86:2545. description:Body size ratios between predators and their prey,

38. Mammal abundance indices in the northern portion of the Great Basin

name:great-basin-mammal-abundance reference:https://figshare.com/articles/Data_Paper_Data_Paper/3525485 citation:Rebecca A. Bartel, Frederick F. Knowlton, and Charles Stoddart. 2005. Mammal abundance indices in the northern portion of the Great Basin, 1962-1993. Ecology 86:3130. description:Indices of abundance of selected mammals obtained for two study areas within the Great Basin.

39. Portal Project Data (Ernest et al. 2016)

name:

portal-dev

reference:

https://github.com/weecology/PortalData

citation:

19. 11. 13. Ernest, G. M. Yenni, G. Allington, E. M. Christensen, K. Geluso, J. R. Goheen, M. R. Schutzenhofer, S. R. Supp, K. M. Thibault, James H. Brown, and T. J. Valone. 2016. Long-term monitoring and experimental manipulation of a Chihuahuan desert ecosystem near Portal, Arizona (1977-2013). Ecology 97:1082.

description:

The data set represents a Desert ecosystems using the composition and abundances of ants, plants, and rodents has occurred continuously on 24 plots.

40. Prairie-forest ecotone of eastern Kansas/Foster Lab

name:prairie-forest reference:https://foster.ku.edu/ltreb-datasets citation:PI: Bryan L. Foster, University of Kansas, bfoster@ku.edu description:Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas (NSF LTREB # 0950100)

41. Demography of the endemic mint Dicerandra frutescens in Florida scrub

name:dicerandra-frutescens reference:https://figshare.com/articles/Data_Paper_Data_Paper/3529460 citation:Eric S. Menges. 2008. Demography of the endemic mint Dicerandra frutescens in Florida scrub. Ecology 89:1474. description:Study of the demography of Dicerandra frutescens, an endemic and endangered mint restricted to Florida scrub

42. Biovolumes for freshwater phytoplankton - Colin et al. 2014

name:phytoplankton-size reference:https://figshare.com/articles/Data_Paper_Data_Paper/3560628 citation:Colin T. Kremer, Jacob P. Gillette, Lars G. Rudstam, Pal Brettum, and Robert Ptacnik. 2014. A compendium of cell and natural unit biovolumes for >1200 freshwater phytoplankton species. Ecology 95:2984. description:Sampling phytoplankton communities basing on cell size.

43. Mammal Life History Database - Ernest, et al., 2003

name:

mammal-life-hist

reference:

mammal-life-hist’s home link.

citation:

19. 11. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.

description:

The purpose of this data set was to compile general life history characteristics for a variety of mammalian species to perform comparative life history analyses among different taxa and different body size groups.

44. Wine Composition

name:wine-composition reference:Exploration, Classification and Correlation. Institute of Pharmaceutical citation:Forina, M. et al, PARVUS - An Extendible Package for Data description:A chemical analysis of wines grown in the same region in Italy but derived from three different cultivators.

45. Long-term population dynamics of individually mapped Sonoran Desert winter annuals from the Desert Laboratory, Tucson AZ

name:sonoran-desert reference:http://www.eebweb.arizona.edu/faculty/venable/LTREB/LTREB%20data.htm citation: description:Long-term population dynamics of individually mapped Sonoran Desert winter annuals from the Desert Laboratory, Tucson AZ

46. Sonoran Desert Lab perennials vegetation plots

name:veg-plots-sdl reference:https://figshare.com/articles/Data_Paper_Data_Paper/3555756 citation:Susana Rodriguez-Buritica, Helen Raichle, Robert H. Webb, Raymond M. Turner, and D. Lawrence Venable. 2013. One hundred and six years of population and community dynamics of Sonoran Desert Laboratory perennials. Ecology 94:976. description:The data set constitutes all information associated with the Spalding-Shreve permanent vegetation plots from 1906 through 2012, which is the longest-running plant monitoring program in the world.

47. Partners_In_Flight_Species_Assessment_Data

name:partners-in-flight reference:http://rmbo.org/pifassessment/Database.aspx citation:Partners in Flight. 2017. Avian Conservation Assessment Database, version 2017. Available at http://pif.birdconservancy.org/ACAD. Accessed on 19.2.2018 description:The Partners in Flight (PIF) Species Assessment Database is now the Avian Conservation Assessment Database, Whereas the Species Assessment Database contained information only on landbirds in Canada, USA and Mexico, the Avian Conservation Assessment Database contains assessment data for all North American birds from Canada to Panama.

48. Database of Vertebrate Home Range Sizes - Tamburello et al., 2015

name:home-ranges reference:http://datadryad.org/resource/doi:10.5061/dryad.q5j65/1 citation:Tamburello N, Cote IM, Dulvy NK (2015) Energy and the scaling of animal space use. The American Naturalist 186(2):196-211. http://dx.doi.org/10.1086/682070. description:Database of mean species masses and corresponding empirically measured home range sizes for 569 vertebrate species from across the globe, including birds, mammals, reptiles, and fishes.

49. Fire-related traits for plant species of the Mediterranean Basin. Ecology 90:1420

name:

mediter-basin-plant-traits

reference:

https://figshare.com/articles/Data_Paper_Data_Paper/3531092

citation:

19. Paula, M. Arianoutsou, D. Kazanis, Ç. Tavsanoglu, F. Lloret, C. Buhk, F. Ojeda, B. Luna, J. M. Moreno, A. Rodrigo, J. M. Espelta, S. Palacio, B. Fernández-Santos,, P. M. Fernandes, and J. G. Pausas. 2009. Fire-related traits for plant species of the Mediterranean Basin. Ecology 90:1420.

description:

This data set compiles the most updated and comprehensive information on fire-related traits for vascular plant species of the Mediterranean Basin

50. USDA plant list - taxonomy for US plant species

name:plant-taxonomy-us reference:http://plants.usda.gov citation:USDA, NRCS. 2017. The PLANTS Database (http://plants.usda.gov, DATEOFDOWNLOAD). National Plant Data Team, Greensboro, NC 27401-4901 USA. description:Plant taxonomy data for the United States from the USDA plants website

51. species data on densities and percent cover in the 60 experimental plots from 1996 to 2002

name:macroalgal-communities reference:https://figshare.com/articles/Data_Paper_Data_Paper/3526004 citation:Peter S. Petraitis and Nicholas Vidargas. 2006. Marine intertidal organisms found in experimental clearings on sheltered shores in the Gulf of Maine, USA. Ecology 87:796. description:Experimental clearings in macroalgal stands were established in 1996 to determine if mussel beds and macroalgal stands on protected intertidal shores of New England represent alternative community states

52. Nematode traits and environmental constraints in 200 soil systems

name:nematode-traits reference:https://figshare.com/articles/Data_Paper_Data_Paper/3552057 citation:Christian Mulder and J. Arie Vonk. 2011. Nematode traits and environmental constraints in 200 soil systems:scaling within the 60–6000 µm body size range. Ecology 92:2004. description:This data set includes information on taxonomy, life stage, sex, feeding habit, trophic level, geographic location, sampling period, ecosystem type, soil type, and soil chemistry

53. Miscellaneous Abundance Database (figshare 2012)

name:community-abundance-misc reference:Not available citation:Baldridge, Elita, A Data-intensive Assessment of the Species Abundance Distribution(2013). All Graduate Theses and Dissertations. Paper 4276. description:Community abundance data for fish, reptiles, amphibians, beetles, spiders, and birds, compiled from the literature by Elita Baldridge.

54. The distribution and host range of the pandemic disease chytridiomycosis in Australia, spanning surveys from 1956-2007.

name:chytr-disease-distr reference:https://figshare.com/articles/Data_Paper_Data_Paper/3547077 citation:Kris Murray, Richard Retallick, Keith R. McDonald, Diana Mendez, Ken Aplin, Peter Kirkpatrick, Lee Berger, David Hunter, Harry B. Hines, R. Campbell, Matthew Pauza, Michael Driessen, Richard Speare, Stephen J. Richards, Michael Mahony, Alastair Freeman, Andrea D. Phillott, Jean-Marc Hero, Kerry Kriger, Don Driscoll, Adam Felton, Robert Puschendorf, and Lee F. Skerratt. 2010. The distribution and host range of the pandemic disease chytridiomycosis in Australia, spanning surveys from 1956-2007. Ecology 91:1557. description:The data is of a distribution and host range of this invasive disease in Australia

55. Mapped plant quadrat time-series from Montana (Anderson et al. 2011)

name:mapped-plant-quads-mt reference:https://figshare.com/articles/Data_Paper_Data_Paper/3551799 citation:Jed Anderson, Lance Vermeire, and Peter B. Adler. 2011. Fourteen years of mapped, permanent quadrats in a northern mixed prairie, USA. Ecology 92:1703. description:Long term plant quadrats of northern mixed prairie in Montana.

56. Spatial Population Data Alpine Butterfly - Matter et al 2014

name:butterfly-population-network reference:butterfly-population-network’s home link. citation:Matter, Stephen F., Nusha Keyghobadhi, and Jens Roland. 2014. Ten years of abundance data within a spatial population network of the alpine butterfly, Parnassius smintheus. Ecology 95:2985. Ecological Archives E095-258. description:Stephen F. Matter, Nusha Keyghobadhi, and Jens Roland. 2014. Ten years of abundance data within a spatial population network of the alpine butterfly, Parnassius smintheus. Ecology 95:2985.

57. Breed-Bird-Survey-nlcd Data

name:breed-bird-survey-nlcd reference:https://figshare.com/articles/Data_Paper_Data_Paper/3554424 citation:Michael F. Small, Joseph A. Veech, and Jennifer L. R. Jensen. 2012. Local landscape composition and configuration around North American Breeding Bird Survey routes. Ecology 93:2298. description:Landcover data for all North American Breeding Bird Survey routes from the 2006 National Land Cover Database at buffers from 200 m to 10 km..

58. Michigan forest canopy dynamics plots - Woods et al. 2009

name:forest-plots-michigan reference:forest-plots-michigan’s home link. citation:Kerry D. Woods. 2009. Multi-decade, spatially explicit population studies of canopy dynamics in Michigan old-growth forests. Ecology 90:3587. description:The data set provides stem infomation from a regular grid of 256 permanent plots includes about 20% of a 100-ha old-growth forest at the Dukes Research Natural Area in northern Michigan, USA.

59. Car Evaluation

name:car-eval reference:http://archive.ics.uci.edu/ml/datasets/Car+Evaluation citation:Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. description:A database useful for testing constructive induction and structure discovery methods.

60. BUPA liver disorders

name:bupa-liver-disorders reference:https://archive.ics.uci.edu/ml/datasets/Liver+Disorders citation:Richard S. Forsyth, 8 Grosvenor Avenue, Mapperley Park , Nottingham NG3 5DX, 0602-621676 description:The first 5 variables are all blood tests which are thought to be sensitive to liver disorders that might arise from excessive alcohol consumption. Each line in the dataset constitutes the record of a single male individual. The 7th field (selector) has been widely misinterpreted in the past as a dependent variable representing presence or absence of a liver disorder. This is incorrect. The 7th field was created by BUPA researchers as a train/test selector. It is not suitable as a dependent variable for classification. The dataset does not contain any variable representing presence or absence of a liver disorder.

61. Masses of Mammals (Smith et al. 2003)

name:mammal-masses reference:https://figshare.com/articles/Data_Paper_Data_Paper/3523112 citation:Felisa A. Smith, S. Kathleen Lyons, S. K. Morgan Ernest, Kate E. Jones, Dawn M. Kaufman, Tamar Dayan, Pablo A. Marquet, James H. Brown, and John P. Haskell. 2003. Body mass of late Quaternary mammals. Ecology 84:3403. description:A data set of compiled body mass information for all mammals on Earth.

62. Fish parasite host ecological characteristics (Strona, et al., 2013)

name:fish-parasite-hosts reference:https://figshare.com/articles/Data_Paper_Data_Paper/3555378 citation:Giovanni Strona, Maria Lourdes D. Palomares, Nicolas Bailly, Paolo Galli, and Kevin D. Lafferty. 2013. Host range, host ecology, and distribution of more than 11800 fish parasite species. Ecology 94:544. description:The data set includes 38008 fish parasite records (for Acanthocephala, Cestoda, Monogenea, Nematoda, Trematoda) compiled from scientific literature.

63. Forest fire data for Montesinho natural park in Portugal

name:

forest-fires-portugal

reference:

http://archive.ics.uci.edu/ml/datasets/Forest+Fires

citation:

16. Cortez and A. Morais. A Data Mining Approach to Predict Forest Fires using Meteorological Data. In J. Neves, M. F. Santos and J. Machado Eds., New Trends in Artificial Intelligence, Proceedings of the 13th EPIA 2007 - Portuguese Conference on Artificial Intelligence, December, Guimaraes, Portugal, pp. 512-523, 2007. APPIA, ISBN-13 978-989-95618-0-9.

description:

A database for regression analysis with the aim of predicting burned areas of forestry using meteorological and other data.

64. New York City TreesCount

name:nyc-tree-count reference:https://www.nycgovparks.org/trees/treescount citation:TreeCount 2015 is citizen science project of NYC Parks’[https://www.nycgovparks.org/trees/treescount]. description:Dataset consist of every street tree of New York City on the block

65. Barnacle, fucoid, and mussel recruitment in the Gulf of Maine, USA, from 1997 to 2007

name:marine-recruitment-data reference:https://figshare.com/articles/Data_Paper_Data_Paper/3530633 citation:Peter S. Petraitis, Harrison Liu, and Erika C. Rhile. 2009. Barnacle, fucoid, and mussel recruitment in the Gulf of Maine, USA, from 1997 to 2007. Ecology 90:571. description:This data set provides access to recruitment data collected in the experimental plots from 1997 to 2007

66. Foraging attributes for birds and mammals (Wilman, et al., 2014)

name:elton-traits reference:elton-traits’s home link. citation:Hamish Wilman, Jonathan Belmaker, Jennifer Simpson, Carolina de la Rosa, Marcelo M. Rivadeneira, and Walter Jetz. 2014. EltonTraits 1.0: Species-level foraging attributes of the world’s birds and mammals. Ecology 95:2027. description:Characterization of species by physiological, behavioral, and ecological attributes that are subjected to varying evolutionary and ecological constraints and jointly determine their role and function in ecosystems.

67. Transparency and Open Data Portals of Brazilian states and municipalities

name:transparencia-dados-abertos-brasil reference:https://github.com/augusto-herrmann/transparencia-dados-abertos-brasil citation:Augusto Herrmann, Transparency and Open Data Portals of Brazilian states and municipalities, (2017), GitHub repository, https://github.com/augusto-herrmann/transparencia-dados-abertos-brasil description:Tabelas com o levantamento de portais estaduais e municipais de transparência e dados abertos, feito originalmente por Rodrigo Klein em sua tese de doutorado na PUC/RS, em 2017

68. The LakeCat Dataset

name:lakecats-final-tables reference:https://www.epa.gov/national-aquatic-resource-surveys/lakecat citation:Hill, Ryan A., Marc H. Weber, Rick Debbout, Scott G. Leibowitz, Anthony R. Olsen. 2018. The Lake-Catchment (LakeCat) Dataset: characterizing landscape features for lake basins within the conterminous USA. Freshwater Science doi:10.1086/697966. description:This current lakecat dataset has 136 local catchment (Cat) and 136 watershed (Ws) metrics making a total of 272 metrics.

69. Cancer Rates Lake County

name:lake-county-illinois-cancer-rates reference:https://catalog.data.gov/dataset/cancer-rates citation: description:geospatial data of cancer rates in Lake County, Illinois

70. Fray Jorge community ecology database (Kelt et al. 2013)

name:

fray-jorge-ecology

reference:

fray-jorge-ecology’s home link.

citation:

4. 1. Kelt, P. L. Meserve, J. R. Gutierrez, W. Bryan Milstead, and M. A. Previtali. 2013. Long-term monitoring of mammals in the face of biotic and abiotic influences at a semiarid site in north-central Chile. Ecology 94:977. http://dx.doi.org/10.1890/12-1811.1.

description:

Long-term monitoring of small mammal and plant communities in the face of biotic and abiotic influences at a semiarid site in north-central Chile.

71. Iris Plants Database

name:

iris

reference:

https://archive.ics.uci.edu/ml/datasets/iris

citation:

18. 1. Fisher. 1936. The Use of Multiple Measurements in Taxonomic Problems. and Asuncion, A. & Newman, D.J. (2007). UCI Machine Learning Repository [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, School of Information and Computer Science.

description:

Famous dataset from R. A. Fisher. This dataset has been corrected. Information Source: Asuncion, A. & Newman, D.J. (2007). UCI Machine Learning Repository [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, School of Information and Computer Science.

72. Shortgrass steppe mapped plants quads - Chu et al. 2013

name:mapped-plant-quads-co reference:https://figshare.com/articles/Data_Paper_Data_Paper/3556779 citation:Cover, density, and demographics of shortgrass steppe plants mapped 1997-2010 in permanent grazed and ungrazed quadrats. Chengjin Chu, John Norman, Robert Flynn, Nicole Kaplan, William K. Lauenroth, and Peter B. Adler. Ecology 2013 94:6, 1435-1435. description:This data set maps and analyzes demographic rates of many common plant species in the shortgrass steppe of North America under grazed and ungrazed conditions.

73. Vascular plant composition - McGlinn, et al., 2010

name:plant-comp-ok reference:https://figshare.com/articles/Data_Paper_Data_Paper/3547209 citation:Daniel J. McGlinn, Peter G. Earls, and Michael W. Palmer. 2010. A 12-year study on the scaling of vascular plant composition in an Oklahoma tallgrass prairie. Ecology 91:1872. description:The data is part of a monitoring project on vascular plant composition at the Tallgrass Prairie Preserve in Osage County, Oklahoma, USA.

74. Vertnet Reptiles

name:vertnet-reptiles reference:http://vertnet.org/resources/datatoolscode.html citation:Bloom, D., Wieczorek J., Russell, L. (2016). VertNet_Reptilia_Sept. 2016. CyVerse Data Commons. http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/VertNet_Reptilia_Sep2016 description:Compilation of digitized museum records of reptiles including locations, dates of collection, and some trait data.

75. USGS North American Breeding Bird Survey

name:breed-bird-survey reference:http://www.pwrc.usgs.gov/BBS/ citation:Pardieck, K.L., D.J. Ziolkowski Jr., M.-A.R. Hudson. 2015. North American Breeding Bird Survey Dataset 1966 - 2014, version 2014.0. U.S. Geological Survey, Patuxent Wildlife Research Center description:A Cooperative effort between the U.S. Geological Survey’s Patuxent Wildlife Research Center and Environment Canada’s Canadian Wildlife Service to monitor the status and trends of North American bird populations.

76. PREDICTS Database

name:predicts reference:http://data.nhm.ac.uk/dataset/902f084d-ce3f-429f-a6a5-23162c73fdf7 citation:Lawrence N Hudson; Tim Newbold; Sara Contu; Samantha L L Hill et al. (2016). Dataset: The 2016 release of the PREDICTS database. http://dx.doi.org/10.5519/0066354 description:A dataset of 3,250,404 measurements, collated from 26,114 sampling locations in 94 countries and representing 47,044 species.

77. Global wood density database - Zanne et al. 2009

name:wood-density reference:http://datadryad.org/resource/doi:10.5061/dryad.234 citation:Chave J, Coomes DA, Jansen S, Lewis SL, Swenson NG, Zanne AE (2009) Towards a worldwide wood economics spectrum. Ecology Letters 12(4): 351-366. http://dx.doi.org/10.1111/j.1461-0248.2009.01285.x and Zanne AE, Lopez-Gonzalez G, Coomes DA, Ilic J, Jansen S, Lewis SL, Miller RB, Swenson NG, Wiemann MC, Chave J (2009) Data from: Towards a worldwide wood economics spectrum. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.234 description:A collection and collation of data on the major wood functional traits, including the largest wood density database to date (8412 taxa), mechanical strength measures and anatomical features, as well as clade-specific features such as secondary chemistry.

78. Vertnet Mammals

name:vertnet-mammals reference:http://vertnet.org/resources/datatoolscode.html citation:Bloom, D., Wieczorek J., Russell, L. (2016). VertNet_Mammals_Sept. 2016. CyVerse Data Commons. http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/VertNet_Mammals_Sep2016 description:Compilation of digitized museum records of mammals including locations, dates of collection, and some trait data.

79. Commercial Fisheries Monthly Trade Data by Product, Country/Association

name:fao-global-capture-product reference:http://www.fao.org/fishery/statistics/global-capture-production/ citation:FAO. 2018. FAO yearbook. Fishery and Aquaculture Statistics 2016/FAO annuaire. Statistiques des pêches et de l’aquaculture 2016/FAO anuario. Estadísticas de pesca y acuicultura 2016. Rome/Roma. 104pp. description:Commercial Fisheries statistics provides a summary of commercial fisheries product data by individual country.

80. 3D Elevation Program (3DEP) high-quality U.S. Geological Survey topographic data

name:usgs-elevation reference:https://pubs.er.usgs.gov/publication/fs20163022 citation:Lukas, Vicki, Stoker, J.M., 2016, 3D Elevation Program—Virtual USA in 3D: U.S. Geological Survey Fact Sheet 2016–3022, 1 p., http://dx.doi.org/10.3133/fs20163022. description:The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses lidar to create a virtual reality maps.

81. Aquatic Animal Excretion

name:aquatic-animal-excretion reference:http://onlinelibrary.wiley.com/doi/10.1002/ecy.1792/abstract citation:Vanni, M. J., McIntyre, P. B., Allen, D., Arnott, D. L., Benstead, J. P., Berg, D. J., Brabrand, Å., Brosse, S., Bukaveckas, P. A., Caliman, A., Capps, K. A., Carneiro, L. S., Chadwick, N. E., Christian, A. D., Clarke, A., Conroy, J. D., Cross, W. F., Culver, D. A., Dalton, C. M., Devine, J. A., Domine, L. M., Evans-White, M. A., Faafeng, B. A., Flecker, A. S., Gido, K. B., Godinot, C., Guariento, R. D., Haertel-Borer, S., Hall, R. O., Henry, R., Herwig, B. R., Hicks, B. J., Higgins, K. A., Hood, J. M., Hopton, M. E., Ikeda, T., James, W. F., Jansen, H. M., Johnson, C. R., Koch, B. J., Lamberti, G. A., Lessard-Pilon, S., Maerz, J. C., Mather, M. E., McManamay, R. A., Milanovich, J. R., Morgan, D. K. J., Moslemi, J. M., Naddafi, R., Nilssen, J. P., Pagano, M., Pilati, A., Post, D. M., Roopin, M., Rugenski, A. T., Schaus, M. H., Shostell, J., Small, G. E., Solomon, C. T., Sterrett, S. C., Strand, O., Tarvainen, M., Taylor, J. M., Torres-Gerald, L. E., Turner, C. B., Urabe, J., Uye, S.-I., Ventelä, A.-M., Villeger, S., Whiles, M. R., Wilhelm, F. M., Wilson, H. F., Xenopoulos, M. A. and Zimmer, K. D. (2017), A global database of nitrogen and phosphorus excretion rates of aquatic animals. Ecology. Accepted Author Manuscript. doi:10.1002/ecy.1792 description:Dataset containing the nutrient cycling rates of individual animals.

82. Gulf of Maine intertidal density/cover (Petraitis et al. 2008)

name:intertidal-abund-me reference:intertidal-abund-me’s home link. citation:Peter S. Petraitis, Harrison Liu, and Erika C. Rhile. 2008. Densities and cover data for intertidal organisms in the Gulf of Maine, USA, from 2003 to 2007. Ecology 89:588. description:The data on densities and percent cover in the 60 experimental plots from 2003 to 2007 and to update data from 1996 to 2002 that are already published in Ecological Archives.Includes densities of mussels, herbivorous limpet, herbivorous snails, predatory snail, barnacle , fucoid algae and percent cover by mussels, barnacles, fucoids, and other sessile organisms.

83. vertnet:

name:vertnet reference:http://vertnet.org/resources/datatoolscode.html citation:Not currently available description:

84. Mammal Super Tree

name:mammal-super-tree reference:http://doi.org/10.1111/j.1461-0248.2009.01307.x citation:Fritz, S. A., Bininda-Emonds, O. R. P. and Purvis, A. (2009), Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecology Letters, 12: 538-549. doi:10.1111/j.1461-0248.2009.01307.x description:Mammal Super Tree from Fritz, S.A., O.R.P Bininda-Emonds, and A. Purvis. 2009. Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecology Letters 12:538-549

85. Commercial Fisheries Monthly Trade Data by Product, Country/Association

name:noaa-fisheries-trade reference:noaa-fisheries-trade’s home link. citation:No known Citation description:Commercial Fisheries statistics provides a summary of commercial fisheries product data by individual country.

86. Commercial Fisheries Monthly Trade Data by Product, Country/Association

name:biotimesql reference:https://zenodo.org/record/1095628#.WskN7dPwYyn citation:Dornelas M, Antão LH, Moyes F, et al. BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology & Biogeography. 2018; 00:1 - 26. https://doi.org/10.1111/geb.12729. description:The BioTIME database has species identities and abundances in ecological assemblages through time.

87. Marine Predator and Prey Body Sizes - Barnes et al. 2008

name:

predator-prey-size-marine

reference:

predator-prey-size-marine’s home link.

citation:

3. Barnes, D. M. Bethea, R. D. Brodeur, J. Spitz, V. Ridoux, C. Pusineri, B. C. Chase, M. E. Hunsicker, F. Juanes, A. Kellermann, J. Lancaster, F. Menard, F.-X. Bard, P. Munk, J. K. Pinnegar, F. S. Scharf, R. A. Rountree, K. I. Stergiou, C. Sassa, A. Sabates, and S. Jennings. 2008. Predator and prey body sizes in marine food webs. Ecology 89:881.

description:

The data set contains relationships between predator and prey size which are needed to describe interactions of species and size classes in food webs.

88. PRISM Climate Data

name:prism-climate reference:http://prism.oregonstate.edu/ citation:Not currently available description:The PRISM data set represents climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns.

89. Amniote life History database

name:amniote-life-hist reference:amniote-life-hist’s home link. citation:Myhrvold, N.P., Baldridge, E., Chan, B., Sivam, D., Freeman, D.L. and Ernest, S.M., 2015. An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles:Ecological Archives E096-269. Ecology, 96(11), pp.3109-000. description:Compilation of life history traits for birds, mammals, and reptiles.

90. BAAD: a Biomass And Allometry Database for woody plants

name:biomass-allometry-db reference:https://doi.org/10.6084/m9.figshare.c.3307692.v1 citation:Falster, D.S., Duursma, R.A., Ishihara, M.I., Barneche, D.R., FitzJohn, R.G., Varhammar, A., Aiba, M., Ando, M., Anten, N., Aspinwall, M.J. and Baltzer, J.L., 2015. BAAD: a Biomass And Allometry Database for woody plants. description:The data set is a Biomass and allometry database (BAAD) for woody plants containing 259634 measurements collected in 176 different studies from 21084 individuals across 678 species.

91. Vertnet Amphibians

name:vertnet-amphibians reference:http://vertnet.org/resources/datatoolscode.html citation:Bloom, D., Wieczorek J., Russell, L. (2016). VertNet_Amphibia_Sept. 2016. CyVerse Data Commons. http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/VertNet_Amphibia_Sep2016 description:Compilation of digitized museum records of amphibians including locations, dates of collection, and some trait data.

92. Alwyn H. Gentry Forest Transect Dataset

name:gentry-forest-transects reference:http://www.mobot.org/mobot/research/gentry/welcome.shtml citation:Phillips, O. and Miller, J.S., 2002. Global patterns of plant diversity: Alwyn H. Gentry’s forest transect data set. Missouri Botanical Press. description:

93. Vertnet Birds

name:vertnet-birds reference:http://vertnet.org/resources/datatoolscode.html citation:Bloom, D., Wieczorek J., Russell, L. (2016). VertNet_Aves_Sept. 2016. CyVerse Data Commons. http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/VertNet_Aves_Sep2016 description:Compilation of digitized museum records of birds including locations, dates of collection, and some trait data.

94. Tree growth, mortality, physical condition - Clark, 2006

name:la-selva-trees reference:https://doi.org/10.6084/m9.figshare.c.3299324.v1 citation:David B. Clark and Deborah A. Clark. 2006. Tree growth, mortality, physical condition, and microsite in an old-growth lowland tropical rain forest. Ecology 87:2132. description:The data set helps to examine the post-establishment ecology of 10 species of tropical wet forest trees selected to span a range of predicted life history patterns at the La Selva Biological Station in Costa Rica.

95. Pantheria (Jones et al. 2009)

name:pantheria reference:pantheria’s home link. citation:Kate E. Jones, Jon Bielby, Marcel Cardillo, Susanne A. Fritz, Justin O’Dell, C. David L. Orme, Kamran Safi, Wes Sechrest, Elizabeth H. Boakes, Chris Carbone, Christina Connolly, Michael J. Cutts, Janine K. Foster, Richard Grenyer, Michael Habib, Christopher A. Plaster, Samantha A. Price, Elizabeth A. Rigby, Janna Rist, Amber Teacher, Olaf R. P. Bininda-Emonds, John L. Gittleman, Georgina M. Mace, and Andy Purvis. 2009. PanTHERIA:a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648. description:PanTHERIA is a data set of multispecies trait data from diverse literature sources and also includes spatial databases of mammalian geographic ranges and global climatic and anthropogenic variables.

96. Load US Census Boundary and Attribute Data as ‘tidyverse’ and ‘sf’-Ready Data Frames

name:tidycensus reference:https://github.com/walkerke/tidycensus citation: description:An integrated R interface to the decennial US Census and American Community Survey APIs andthe US Census Bureau’s geographic boundary files. Allows R users to return Census and ACS data astidyverse-ready data frames, and optionally returns a listcolumn with feature geometry for all Censusgeographies.

97. Indian Forest Stand Structure and Composition (Ramesh et al. 2010)

name:

forest-plots-wghats

reference:

forest-plots-wghats’s home link.

citation:

2. 18. Ramesh, M. H. Swaminath, Santoshgouda V. Patil, Dasappa, Raphael Pelissier, P. Dilip Venugopal, S. Aravajy, Claire Elouard, and S. Ramalingam. 2010. Forest stand structure and composition in 96 sites along environmental gradients in the central Western Ghats of India. Ecology 91:3118.

description:

This data set reports woody plant species abundances in a network of 96 sampling sites spread across 22000 km2 in central Western Ghats region, Karnataka, India.

98. Forest Inventory and Analysis

name:forest-inventory-analysis reference:http://fia.fs.fed.us/ citation:DATEOFDOWNLOAD. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station. [Available only on internet: http://apps.fs.fed.us/fiadb-downloads/datamart.html] description:WARNING: This dataset requires downloading many large files and will probably take several hours to finish installing.

99. A Southern Ocean dietary database

name:socean-diet-data reference:https://figshare.com/articles/Full_Archive/3551304 citation:Ben Raymond, Michelle Marshall, Gabrielle Nevitt, Chris L. Gillies, John van den Hoff, Jonathan S. Stark, Marcel Losekoot, Eric J. Woehler, and Andrew J. Constable. 2011. A Southern Ocean dietary database. Ecology 92:1188. description:Diet-related data from published and unpublished data sets and studies

100. USGS North American Breeding Bird Survey 50 stop

name:breed-bird-survey-50stop reference:http://www.pwrc.usgs.gov/BBS/ citation:Pardieck, K.L., D.J. Ziolkowski Jr., M.-A.R. Hudson. 2015. North American Breeding Bird Survey Dataset 1966 - 2014, version 2014.0. U.S. Geological Survey, Patuxent Wildlife Research Center. description:A Cooperative effort between the U.S. Geological Survey’s Patuxent Wildlife Research Center and Environment Canada’s Canadian Wildlife Service to monitor the status and trends of North American bird populations.

101. Food web including metazoan parasites for a brackish shallow water ecosystem in Germany and Denmark

name:

flensburg-food-web

reference:

https://figshare.com/articles/Full_Archive/3552066

citation:

3. Dieter Zander, Neri Josten, Kim C. Detloff, Robert Poulin, John P. McLaughlin, and David W. Thieltges. 2011. Food web including metazoan parasites for a brackish shallow water ecosystem in Germany and Denmark. Ecology 92:2007.

description:

This data is of a food web for the Flensburg Fjord, a brackish shallow water inlet on the Baltic Sea, between Germany and Denmark.

102. USA National Phenology Network

name:npn reference:http://www.usanpn.org/results/data citation:Schwartz, M. D., Ault, T. R., & J. L. Betancourt, 2012: Spring Onset Variations and Trends in the Continental USA: Past and Regional Assessment Using Temperature-Based Indices. International Journal of Climatology (published online, DOI: 10.1002/joc.3625). description:The data set was collected via Nature’s Notebook phenology observation program (2009-present), and (2) Lilac and honeysuckle data (1955-present)

103. Tree demography in Western Ghats, India - Pelissier et al. 2011

name:tree-demog-wghats reference:tree-demog-wghats’s home link. citation:Raphael Pelissier, Jean-Pierre Pascal, N. Ayyappan, B. R. Ramesh, S. Aravajy, and S. R. Ramalingam. 2011. Twenty years tree demography in an undisturbed Dipterocarp permanent sample plot at Uppangala, Western Ghats of India. Ecology 92:1376. description:A data set on demography of trees monitored over 20 years in Uppangala permanent sample plot (UPSP).

104. Vertnet Fishes

name:vertnet-fishes reference:http://vertnet.org/resources/datatoolscode.html citation:Bloom, D., Wieczorek J., Russell, L. (2016). VertNet_Fishes_Sept. 2016. CyVerse Data Commons. http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/VertNet_Fishes_Sep2016 description:Compilation of digitized museum records of fishes including locations, dates of collection, and some trait data.

105. A database on the life history traits of the Northwest European flora

name:plant-life-hist-eu reference:http://www.uni-oldenburg.de/en/biology/landeco/research/projects/leda/ citation:KLEYER, M., BEKKER, R.M., KNEVEL, I.C., BAKKER, J.P, THOMPSON, K., SONNENSCHEIN, M., POSCHLOD, P., VAN GROENENDAEL, J.M., KLIMES, L., KLIMESOVA, J., KLOTZ, S., RUSCH, G.M., HERMY, M., ADRIAENS, D., BOEDELTJE, G., BOSSUYT, B., DANNEMANN, A., ENDELS, P., GoeTZENBERGER, L., HODGSON, J.G., JACKEL, A-K., KueHN, I., KUNZMANN, D., OZINGA, W.A., RoeMERMANN, C., STADLER, M., SCHLEGELMILCH, J., STEENDAM, H.J., TACKENBERG, O., WILMANN, B., CORNELISSEN, J.H.C., ERIKSSON, O., GARNIER, E., PECO, B. (2008): The LEDA Traitbase: A database of life-history traits of Northwest European flora. Journal of Ecology 96: 1266-1274 description:The LEDA Traitbase provides information on plant traits that describe three key features of plant dynamics: persistence, regeneration and dispersal.

106. Fia us-virgin-islands, VI

name:fia-us-virgin-islands reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

107. Fire Occurrence FIRESTAT yearly

name:fire-occurrence-firestat-yearly reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210407. FIRESTAT Fire Occurrence - Yearly Update: Fire Occurrence FIRESTAT yearly. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Fire_Occurrence_FIRESTAT_YRLY.xml. description:The FIRESTAT (Fire Statistics System) Fire Occurrence point layer represents ignition points, or points of origin, from which individual wildland fires started on National Forest System lands

108. White Clay Creek – Well Water Levels (1988-2012)

name:white-clay-creek-waterlevels reference:https://czo.stroudcenter.org/data/white-clay-creek-well-water-levels-1988-2012/ citation:Well Water Level data collected by Stroud Water Research Center description:Well Water Level data collected by Stroud Water Research Center

109. The US Forest Service, Forest Health Monitoring, Michigan

name:forest-health-monitoring-michigan reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

110. White Clay Creek – Chlorophyll – Pheophytin (2001-2012)

name:white-clay-creek-chlorophyll reference:https://czo.stroudcenter.org/data/white-clay-creek-chlorophyll-pheophytin-2001-2012/ citation:Newbold, J. D.; Damiano, S. G. (2013). White Clay Creek - Chlorophyll (2001-2012). Stroud Water Research Center. description:Stream Chlorophyll and Pheophytin data collected by Stroud Water Research Center

111. PA Avondale 2N - Soil Moisture, Soil Temperature - NOAA CRN (2011-2015)

name:white-clay-creek-avondale-soil reference:white-clay-creek-avondale-soil’s home link. citation:Bell, J.E., M.A. Palecki, C.B. Baker, W.G. Collins, J.H. Lawrimore, R.D. Leeper, M.E. Hall, J. Kochendorfer, T.P. Meyers, T. Wilson, and H.J. Diamond. 2013: U.S. Climate Reference Network Soil Moisture and Temperature Observations. J. Hydrometeorol., doi: 10.1175/JHM-D-12-0146.1. See http://www.ncdc.noaa.gov/crn/publications.html. description:The U.S. Climate Reference Network (USCRN) developed by the National Oceanic and Atmospheric Administration (NOAA) provide future long-term homogeneous temperature and precipitation observations that can be coupled to long-term historical observations for the detection and attribution of present and future climate change.

112. Fernow Experimental Forest stream chemistry

name:fernow-stream-chemistry reference:https://www.fs.usda.gov/rds/archive/catalog/RDS-2011-0017 citation:Edwards, Pamela J.; Wood, Frederica. 2011. Fernow Experimental Forest stream chemistry. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. Data publication updated 17 August 2017. https://doi.org/10.2737/RDS-2011-0017 description:The data publication contains weekly or biweekly stream water chemistry from nine gauged watersheds on the Fernow Experimental Forest from 1983 to 2015.

113. Prince Edward Island Detailed Soil Survey

name:prince-edward-island-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/3adcf032-7fdb-4301-8d8e-ebf0e0f06e68 citation: description:The Prince Edward Island Detailed Soil Survey is a dataset series describing the spatial distribution of soils and associated landscapes in the Canadian province of Prince Edward Island.

114. The North Carolina Piedmont Forest LTREB Project, Mapped Forest Stands

name:north-carolina-piedmont-mapped-foreset reference:http://labs.bio.unc.edu/Peet/PEL/df.htm citation: description:Mapped Forest Stands of North Carolina Piedmont Forest LTREB Project

115. Fia oregon, OR

name:fia-oregon reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

116. The US Forest Service, Forest Health Monitoring, Rhode Island

name:forest-health-monitoring-rhodeisland reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

117. Fia vermont, VT

name:fia-vermont reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

118. coronavirus-belgium

name:coronavirus-belgium reference:https://epistat.wiv-isp.be/covid/ citation: description:Dataset of COVID-19 in Belgium

119. The US Forest Service, Forest Health Monitoring, Illinois

name:forest-health-monitoring-illinois reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

120. Fernow experimental Forest in central Appalachia. LTREB WS 4 Biomass

name:fernow-biomass reference:http://www.as.wvu.edu/fernow/data.html citation:Tajchman, S.J., H. Fu, J.N. Kochenderfer, and C. Pan. 1995. Spatial characteristics of topography, energy exchange, and forest cover in a central Appalachian watershed. Proceedings, 10th Central Hardwood Forest Conference. USDA Forest Service Northeast Forest Experimental Station General Technical Report NE-197. description:Fernow experimental Forest in central Appalachia. LTREB WS 4 Biomass, See Data policy

121. Maizuru Bay fish community

name:ushio-maizuru-fish-community reference:https://github.com/ong8181/dynamic-stability citation:Ushio M, Hsieh CH, Masuda R, Deyle RE, Ye H, Chang CW, Sugihara G, Kondoh M (2018) Fluctuating interaction entwork and time-varying stability of a natural fish community Nature 554 (7692): 360–363 doi:101038/nature25504 description:Fluctuating interaction network and time-varying stability of a natural fish community

122. Fia american-samoa, AS

name:fia-american-samoa reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

123. Fia puerto-rico, PR

name:fia-puerto-rico reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

124. Fia utah, UT

name:fia-utah reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

125. Fia maryland, MD

name:fia-maryland reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

126. The US Forest Service, Forest Health Monitoring, North Carolina

name:forest-health-monitoring-northcarolina reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

127. The US Forest Service, Forest Health Monitoring, New Hampshire

name:forest-health-monitoring-newhampshire reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

128. Fia virginia, VA

name:fia-virginia reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

129. Fia kansas, KS

name:fia-kansas reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

130. Zipcodes dataset

name:zipcodes reference:http://federalgovernmentzipcodes.us/license.html citation:Coven, D. S., (2012). Free Zipcode Database: [Unique Zipcode | All Locations data file]. Retrieved from http://federalgovernmentzipcodes.us description:Zipcode data

131. Fia idaho, ID

name:fia-idaho reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

132. The USA MTBS Burn Area Boundary

name:mtbs-burn-area-boundary reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20190826. MTBS Burn Area Boundary: MTBS Burn Area Boundary. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.MTBS_BURN_AREA_BOUNDARY.xml. description:The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity)

133. Fia illinois, IL

name:fia-illinois reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

134. Fia palau, PW

name:fia-palau reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

135. Fia michigan, MI

name:fia-michigan reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

136. The US Forest Service, Forest Health Monitoring, Indiana

name:forest-health-monitoring-indiana reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

137. Virgin Islands National Park: Coral Reef: Physical Measurements

name:virgin-islands-coral-physical-measurements reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds P. 2019. Virgin Islands National Park: Coral Reef: Physical Measurements. Environmental Data Initiative. https://doi.org/10.6073/pasta/f68ca3604ca632eabcd31712ca0cd622. Dataset accessed 10/10/2019. description:Virgin Islands National Park Coral Reef Physical measurements, Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

138. The National Atmospheric Deposition Program (NADP) precipitation chemistry

name:nadp-precipitation-chemistry reference:http://nadp.slh.wisc.edu/data/ citation: description:The National Atmospheric Deposition Program (NADP) monitors precipitation chemistry. The data contains long term record of total mercury (Hg), ammonia gas

139. Nova Scotia Detailed Soil Survey

name:nova-scotia-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/083534ca-d5b0-46f5-b540-f3a706dbc2de citation: description:The Nova Scotia Detailed Soil Survey dataset series at a scale of 1:50 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF).

140. Activity Silviculture Timber Stand Improvement

name:activity-silviculture-timber-stand-improvement reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210407. Activity Silviculture Timber Stand Improvement: S_USA.Activity_SilvTSI. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Activity_SilvTSI.xml. description:The SilvTSI (Silviculture Timber Stand Improvement) feature class represents activities associated with the following performance measure: Forest Vegetation Improved (Release, Weeding, and Cleaning, Precommercial Thinning, Pruning and Fertilization).

141. Fia colorado, CO

name:fia-colorado reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

142. The US Forest Service, Forest Health Monitoring, Delaware

name:forest-health-monitoring-delaware reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

143. White Clay Creek Stage, Streamflow or Discharge (1968-2014)

name:white-clay-creek-streamflow reference:white-clay-creek-streamflow’s home link. citation:Continuous streamflow data collected by Stroud Water Research Center description:Continuous streamflow data collected by the Stroud Water Research Center within the 3rd-order research watershed, White Clay Creek above McCue Road.

144. Christina River Basin - Stream Water Chemistry (1977-2017)

name:white-clay-creek-christina-chemistry reference:FILL citation:Kaplan, L. A.; Newbold, J. D.; Aufdenkampe, A. K.; Anderson, B. A.; Damiano, S.G. (2013). Christina River Basin - Stream Water Chemistry (1977-2010). Stroud Water Research Center. description:Stream Chemistry data collected by Stroud Water Research Center

145. Rodent data from trapping webs in the long-term Small Mammal Exclusion Study (SMES) at Jornada Basin LTER, 1995-2007

name:jornada-lter-rodent reference:https://portal.lternet.edu/nis/mapbrowse?packageid=knb-lter-jrn.210086009.74 citation:Bestelmeyer B., D. Lightfoot, R. Schooley. 2019. Rodent data from trapping webs in the long-term Small Mammal Exclusion Study (SMES) at Jornada Basin LTER, 1995-2007. Environmental Data Initiative. https://doi.org/10.6073/pasta/0c38baecb2e10b4fe70d187ba6f08dda. Dataset accessed 1/30/2020. description:This data package contains rodent trapping data from plots with various levels of herbivore exclusion on the Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands.

146. Fia california, CA

name:fia-california reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

147. Fia georgia, GA

name:fia-georgia reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

148. The US Forest Service, Forest Health Monitoring, Maine

name:forest-health-monitoring-maine reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

149. The US Forest Service, Forest Health Monitoring, Vermont

name:forest-health-monitoring-vermont reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

150. The USA MTBS Fire Occurrence Points

name:mtbs-fire-occurrence reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20190826. MTBS Fire Occurrence Points: MTBS Fire Occurrence Points. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.MTBS_FIRE_OCCURRENCE_PT.xml. description:Monitoring Trends in Burn Severity Project

151. Sycamore Creek macroinvertebrate collections after flooding event

name:sycamore-creek-macroinvertebrate reference:https://sustainability.asu.edu/caplter/data/view/knb-lter-cap.375.8/ citation: description:This data shows how long-term climate variability influences the structure and function of desert streams

152. fill

name:nlcd-urban-imperviousness-puerto-rico reference:fill citation:fill description:pr_masked_imperv_10-25-08.img

153. Fia federated-states-micrones, FM

name:fia-federated-states-micrones reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

154. Saskatchewan Detailed Soil Survey

name:saskatchewan-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/3734623c-25c5-4e69-936d-26f764a2807f citation: description:The Saskatchewan Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF)

155. Virgin Islands National Park: Coral Reef: Recruitment Tiles

name:virgin-islands-coral-recruitment-tiles reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds P. 2018. Virgin Islands National Park: Coral Reef: Recruitment Tiles. Environmental Data Initiative. https://doi.org/10.6073/pasta/c22c4c8064634988f680a004e8ed9876. Dataset accessed 10/10/2019. description:Virgin Islands National Park: Coral Reef: Recruitment Tiles, Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

156. Fernow Experimental Forest precipitation chemistry

name:fernow-precipitation-chemistry reference:https://www.fs.usda.gov/rds/archive/catalog/RDS-2011-0016 citation:Edwards, Pamela J.; Wood, Frederica. 2011. Fernow Experimental Forest precipitation chemistry. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. Data publication updated 17 August 2017. https://doi.org/10.2737/RDS-2011-0016 description:The data publication contains weekly precipitation chemistry from two weather stations on the Fernow Experimental Forest from 1983 to 2015

157. British Columbia Detailed Soil Survey

name:british-columbia-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/adf4d26a-9fc0-44c9-ba38-620531ca0dbe citation: description:The British Columbia Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF).

158. The US Forest Service, Forest Health Monitoring, West Virginia

name:forest-health-monitoring-westvirginia reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

159. Christina River Basin – Stream Water Temperatures (2007-2014)

name:white-clay-creek-christina-temperatures reference:white-clay-creek-christina-temperatures’s home link. citation:Sweeney, B.; Funk, D.; Newbold, J. D.; Kaplan, L. A.; Damiano, S. G.; Kline, F.; West, H.(2013). Christina River Basin - Stream Water Temperatures (2007-2012). Stroud Water Research Center. description:Stream Temperature data collected by Stroud Water Research Center

160. The US Forest Service, Forest Health Monitoring, Maryland

name:forest-health-monitoring-maryland reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

161. Fia louisiana, LA

name:fia-louisiana reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

162. Foundation Foods

name:usda-mafcl-fooddatacenteral-foundationfoods reference:usda-mafcl-fooddatacenteral-foundationfoods’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:The data includes nutrient and food component values on a diverse range of ingredient and commodity foods.

163. The US Forest Service, Forest Health Monitoring, Colorado

name:forest-health-monitoring-colorado reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

164. Credit Card Fraud Detection Dataset

name:credit-card-fraud reference:https://www.kaggle.com/mlg-ulb/creditcardfraud citation: description:Anonymized credit card transactions labeled as fraudulent or genuine

165. Fernow Experimental Forest daily air temperature

name:fernow-air-temperature reference:https://www.fs.usda.gov/rds/archive/catalog/RDS-2011-0013 citation:Edwards, Pamela J.; Wood, Frederica. 2011. Fernow Experimental Forest daily air temperature. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. Data publication updated 17 August 2017. https://doi.org/10.2737/RDS-2011-0013 description:The data publication contains daily maximum and minimum air temperature measured at two weather stations on the Fernow Experimental Forest from 1951 to 2015

166. Food and Nutrient Database for Dietary Studies 2013-2014 (FNDDS 2013-2014)

name:usda-mafcl-fooddatacenteral-fndds reference:usda-mafcl-fooddatacenteral-fndds’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:The data shows the nutrient and food component values and weights for foods and beverages reported in America dietary survey component of the National Health and Nutrition Examination Survey

167. Fia south-carolina, SC

name:fia-south-carolina reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

168. The US Forest Service, Forest Health Monitoring, Connecticut

name:forest-health-monitoring-connecticut reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

169. Fia massachusetts, MA

name:fia-massachusetts reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

170. The US Forest Service, Forest Health Monitoring, Idaho

name:forest-health-monitoring-idaho reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

171. The US Forest Service, Forest Health Monitoring, Georgia

name:forest-health-monitoring-georgia reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

172. Fia new-jersey, NJ

name:fia-new-jersey reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

173. BUILDBPS: Facilities and educational data for boston public schools

name:boston-buildbps reference:boston-buildbps’s home link. citation: description:Boston, BuildBPS compiles data that can be used to guide and inform decisions related to school building investments

174. Virgin Islands National Park, Coral Reef, Population Dynamics: Scleractinian corals

name:virgin-islands-coral-yawzi-transects reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds P. 2019. Virgin Islands National Park: Coral Reef: Population Dynamics: Scleractinian corals. Environmental Data Initiative. https://doi.org/10.6073/pasta/8e0b03fdc567b91aa2edc6e875291ff7. Dataset accessed 10/10/2019 description:Population Dynamics of Scleractinian Corals, Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

175. Stroud Water Research Center - Precipitation, Meteorology (1996-2010)

name:white-clay-creek-swrc-meteorology reference:white-clay-creek-swrc-meteorology’s home link. citation:Tsang, Y.-P., Hourly Precipitation at Stroud Water Research Center 1996-2010 description:Meteorological data collected at Stroud Water Research Center

176. Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Program data

name:shortgrass-steppe-lter reference:https://portal.lternet.edu/nis/mapbrowse?packageid=knb-lter-sgs.137.17 citation:Stapp P. 2013. SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2006, ARS Study Number 118. Environmental Data Initiative. https://doi.org/10.6073/pasta/2e311b4e40fea38e573890f473807ba9. Dataset accessed 1/30/2020. description:SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2006, ARS Study Number 118

177. Fia alabama, AL

name:fia-alabama reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

178. fill

name:nlcd-urban-imperviousness-hawaii reference:fill citation:fill description:hi_masked_imperv_9-30-08.img

179. Fia tennessee, TN

name:fia-tennessee reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

180. Virgin Islands National Park: Landscape-scale Variation in Community Structure

name:virgin-islands-coral-landscape-scale reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:N/A description:Percent cover on tiles at landscape-scale sites, Download data after acceptance of MCR LTER Data Use Agreement, http://coralreefs.csun.edu/legal/use-policy/

181. The North Carolina Piedmont Forest LTREB Project, Seedling and Sapling Plots

name:north-carolina-piedmont_seedlng_sampling reference:http://labs.bio.unc.edu/Peet/PEL/df.htm citation: description:The data shows the Seedling and Sapling Plots information from North Carolina Piedmont Forest LTREB Project

182. Virgin Islands National Park: Population Dynamics of Octocorals

name:virgin-islands-coral-octocorals-count reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds, P.J., Tsounis, G. & Lasker, H.R. Hydrobiologia (2016) 767: 347. https://doi.org/10.1007/s10750-015-2555-z description:These data describe coral reef community structure by density based on the analysis of color photographs along the south coast of St. John from as early as 1987, http://coralreefs.csun.edu/legal/use-policy/

183. The US Forest Service, Forest Health Monitoring, Oregon

name:forest-health-monitoring-oregon reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

184. Fia arizona, AZ

name:fia-arizona reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

185. The North Carolina Piedmont Forest LTREB Project, Permanent sample plots

name:north-carolina-piedmont-permanent-plots reference:http://labs.bio.unc.edu/Peet/PEL/df.htm citation: description:The data between 1931 and 1947 permanent sample plots (PSPs) with individually numbered trees were established in the Duke Forest

186. Virgin Islands National Park: Population Projections for Orbicella annularis

name:virgin-islands-coral-population-projections reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds, P.J., 2015. A quarter-century demographic analysis of the Caribbean coral, Orbicella annularis, and projections of population size over the next century. Limnology and Oceanography, 60, pp.840-855. description:Populations Dynamics and Population Projections data, Long-term Coral Reef Community Dynamics, http://coralreefs.csun.edu/legal/use-policy/

187. The US Forest Service, Forest Health Monitoring, Nevada

name:forest-health-monitoring-nevada reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

188. Arsenic contamination of groundwater in Bangladesh data

name:arsenic-contamination-bangladesh reference:http://www.bgs.ac.uk/research/groundwater/health/arsenic/Bangladesh/data.html citation:BGS and DPHE. 2001. Arsenic contamination of groundwater in Bangladesh. Kinniburgh, D G and Smedley, P L (Editors). British Geological Survey Technical Report WC/00/19. British Geological Survey: Keyworth. description:Bangladesh, Arsenic contamination of groundwater

189. Fia wyoming, WY

name:fia-wyoming reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

190. Christina River Basin – Stream Suspended Sediment (1993-2012)

name:white-clay-creek-christina-sediment reference:white-clay-creek-christina-sediment’s home link. citation:Aufdenkampe, A.K.; Newbold, J.D.; Anderson, B. A.; Richardson, D.; Damiano, S.G. (2013). Christina River Basin - Stream Suspended Sediment (1993-2012). Stroud Water Research Center. description:The data contains the total suspended solids (TSS) and Volatile Suspended Solids (VSS) from White Clay Creek near the Stroud Water Research Center, Avondale, PA, USA

191. The US Forest Service, Forest Health Monitoring, South Carolina

name:forest-health-monitoring-southcarolina reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

192. The US Forest Service, Forest Health Monitoring, Pennsylvania

name:forest-health-monitoring-pennsylvania reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

193. COVID-19 Case Surveillance Public Use Data with Geography

name:covid-case-surveillance reference:https://dev.socrata.com/foundry/data.cdc.gov/n8mc-b4w4 citation: description:This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

194. The US Forest Service, Forest Health Monitoring, California

name:forest-health-monitoring-california reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

195. Fernow Experimental Forest daily streamflow

name:fernow-forest-streamflow reference:https://www.fs.usda.gov/rds/archive/catalog/RDS-2011-0015 citation:Edwards, Pamela J.; Wood, Frederica. 2011. Fernow Experimental Forest daily streamflow. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. Data publication updated 17 August 2017. https://doi.org/10.2737/RDS-2011-0015 description:The data contains daily streamflow for nine watersheds on the Fernow Experimental Forest from 1951 to 2015.

196. Fia ohio, OH

name:fia-ohio reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

197. Virgin islands coral scleractinian corals

name:virgin-islands-coral-scleractinian-corals reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:N/A description:Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

198. Fia north-carolina, NC

name:fia-north-carolina reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

199. Fia iowa, IA

name:fia-iowa reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

200. The USA Activity TimberHarvest dataset

name:activity-timberharvest reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210407. Timber Harvests: S_USA.Activity_TimberHarvest. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Activity_TimberHarvest.xml. description:The TimeberHarvest feature class depicts the area planned and accomplished acres treated as a part of the Timber Harvest program of work

201. All FoodData Central data types

name:usda-mafcl-fooddatacenteral-alldatatypes reference:usda-mafcl-fooddatacenteral-alldatatypes’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:The datasets contains files for all of the FoodData Central data types

202. County Emergency Management Offices New York

name:county-emergency-management-offices reference:https://catalog.data.gov/dataset/county-emergency-management-offices citation: description:Dataset lists all contacts for Emergency Management Offices within NYS

203. Yukon Detailed Soil Survey

name:yukon-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/91c39230-fb8d-45f7-8af9-11257a549710 citation: description:The Yukon Detailed Soil Survey dataset series consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF)

204. Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas (NSF LTREB # 0950100)

name:foster-ltreb reference:https://foster.ku.edu/ltreb-datasets citation: description:The data is used towards understanding and predicting the potential effects of accelerated human activity on biological diversity and ecosystem sustainability

205. Ontario Detailed Soil Survey

name:ontario-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/a75c3d6c-354d-436d-999d-431fb3a9de79 citation: description:The Ontario Detailed Soil Survey dataset series is at a scale of 1: 50 000 and consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF).

206. Fia pennsylvania, PA

name:fia-pennsylvania reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

207. Fia north-dakota, ND

name:fia-north-dakota reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

208. Fia indiana, IN

name:fia-indiana reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

209. The New York Times Coronavirus (Covid-19) Data in the United States

name:nytimes-us-covid reference:https://github.com/nytimes/covid-19-data citation:Data from The New York Times, based on reports from state and local health agencies. description:The New York Times’ data files with cumulative counts of coronavirus cases in the United States

210. Virgin Islands National Park: Coral Reef: Decadal-scale changes in community structure from 1987 to 2011

name:virgin-islands-coral-decadal-scale reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds PJ (2013) Decadal-scale changes in the community structure of coral reefs of St. John, US Virgin Islands. Mar Ecol Prog Ser 489:107-123. https://doi.org/10.3354/meps10424 description:Long-term Coral Reef Community Dynamics, Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

211. IATA airport code

name:airport-codes reference:https://datahub.io/core/airport-codes citation: description:Compiled dataset of airport codes from around the world

212. The US Forest Service, Forest Health Monitoring, Wisconsin

name:forest-health-monitoring-wisconsin reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

213. The US Forest Service, Forest Health Monitoring, Florida

name:forest-health-monitoring-florida reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

214. 30 seconds WorldClim variables for WorldClim version 2

name:worldclim-thirty reference:http://worldclim.org/version2 citation:Fick, S.E. and R.J. Hijmans, 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. description:WorldClim variables at 30 seconds, minimum temperature (°C), maximum temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1), water vapor pressure (kPa), Bioclimatic variables

215. Hyperspectral benchmark dataset on soil moisture

name:felix-riese-hyperspectral-soilmoisture reference:https://zenodo.org/record/2530634#.Xf7thC2ZOuU citation:Felix M. Riese and Sina Keller, “Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data,” in 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018, description:Hyperspectral and soil-moisture data from a field campaign based on a soil sample. Karlsruhe (Germany), 2017

216. Titanic: Machine Learning from Disaster

name:titanic reference:https://www.kaggle.com/c/titanic citation: description:Titanic passenger data use to predict survival on the Titanic

217. Fia arkansas, AR

name:fia-arkansas reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

218. The US Forest Service, Forest Health Monitoring, New York

name:forest-health-monitoring-newyork reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

219. The US Forest Service, Forest Health Monitoring, Virginia

name:forest-health-monitoring-virginia reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

220. WorldClim [Bioclimatic] variables for WorldClim version 2

name:worldclim-twofive reference:http://worldclim.org/version2 citation:Fick, S.E. and R.J. Hijmans, 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. description:WorldClim variables at 2.5 minutes, minimum temperature (°C), maximum temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1), water vapor pressure (kPa), Bioclimatic variables

221. Fia kentucky, KY

name:fia-kentucky reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

222. The USA Final Fire Perimeter dataset, National USFS Final Fire Perimeter

name:national-usfs-finalfire-perimeter reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210415. National USFS Final Fire Perimeter: S_USA.FinalFirePerimeter. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.FinalFirePerimeter.xml. description:The FinalFirePerimeter polygon layer represents final mapped wildland fire perimeters

223. Dietary Supplement Ingredient Database (DSID-4),

name:usda-dietary-supplement-ingredient-data reference:https://dietarysupplementdatabase.usda.nih.gov/Data_Files.php citation:US Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory and US Department of Health and Human Services, National Institutes of Health, Office of Dietary Supplements. Dietary Supplement Ingredient Database (DSID) release 4.0, August 2017. Available from: https://dsid.usda.nih.gov description:This is the fourth release of the Dietary Supplement Ingredient Database (DSID-4) which reports national estimates for ingredient levels in dietary supplements (DS), based on chemical analysis

224. Foreign Exchange rates for 2000 to 2019

name:foreign-exchange-rates-2000-2019 reference:https://www.kaggle.com/brunotly/foreign-exchange-rates-per-dollar-20002019 citation: description:Federal Reserve’s time serie of foreign exchange rates per dollar from 2000 to 2019

225. Fia mississippi, MS

name:fia-mississippi reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

226. The US Forest Service, Forest Health Monitoring, Massachusetts

name:forest-health-monitoring-massachusetts reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

227. Rainfall in India

name:rainfall-in-india reference:https://data.gov.in/resources/sub-divisional-monthly-rainfall-1901-2017 citation:India Meteorological Department (IMD) description:Month wise all India rainfall data from 1901-2017. The sub-division wise rainfall and its departure from normal for each month and season has been provided in the data.

228. Fia florida, FL

name:fia-florida reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

229. Whole Watershed Acidification Experiment, Fernow experimental Forest, LTREB

name:fernow-watershed-acidification reference:http://www.as.wvu.edu/fernow/data.html citation: description:Fernow experimental Forest, LTREB, See Data policy

230. FoodData Central Data Supporting Data

name:usda-mafcl-fooddatacenteral-supportingdata reference:usda-mafcl-fooddatacenteral-supportingdata’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:Supporting data for the FoodData Central Data

231. WorldClim variables WorldClim version 2 at 10 minutes (~340 km2)

name:worldclim-ten reference:http://worldclim.org/version2 citation:Fick, S.E. and R.J. Hijmans, 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. description:WorldClim variables at 10 minutes, minimum temperature (°C), maximum temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1), water vapor pressure (kPa), Bioclimatic variables

232. Fia oklahoma, OK

name:fia-oklahoma reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

233. Virgin Islands National Park, Geography of Sites

name:virgin-islands-coral-geography reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:N/A description:This is a reference dataset containing the site locations, year established, and types of surveys, http://coralreefs.csun.edu/legal/use-policy/

234. Global Population Dynamics Database

name:global-population-dynamics reference:https://knb.ecoinformatics.org/view/doi:10.5063/F1BZ63Z8 citation:John Prendergast, Ellen Bazeley-White, Owen Smith, John Lawton, Pablo Inchausti, et al. 2010. The Global Population Dynamics Database. Knowledge Network for Biocomplexity. doi:10.5063/F1BZ63Z8. description:GDPP conatins animal and plant population data, with about five thousand separate time series, population counts, taxonomic details of about 1400 species.

235. The USA Activity SilvicultureReforestation.

name:usa-activity-silvreforestation reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210407. Activity SilvicultureReforestation: S_USA.SilvReforestation. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Activity_SilvReforestation.xml. description:The SilvReforestation feature class represents activities associated with the following performance measure: Forest Vegetation Establishment (Planting, Seeding, Site Preparation for Natural Regeneration and Certification of Natural Regeneration without Site Preparation).

236. COVID-19 in Italy

name:coronavirus-italy reference:https://www.kaggle.com/sudalairajkumar/covid19-in-italy citation: description:Coronavirus Disease 2019 cases in Italy

237. Fia nebraska, NE

name:fia-nebraska reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

238. Test data raster bio1

name:sample-hdf reference:N/A citation:N/A description:Test data sampled from bioclim bio1

239. NTN Site WV18, Rain Chemistry data, National Atmospheric Deposition Program, State of West Virginia (WV)

name:fernow-nadp-rain-chemistry reference:http://nadp.slh.wisc.edu/data/sites/siteDetails.aspx?net=NTN&id=WV18 citation: description:This data is the rain Chemistry data used in Fernow Experimental Forest Monitoring, part of National Atmospheric Deposition Program, State of West Virginia (WV),

240. National Pedon Database Summary Layer

name:canada-soil-survey reference:https://open.canada.ca/data/en/dataset/6457fad6-b6f5-47a3-9bd1-ad14aea4b9e0 citation: description:The Canada National Soil Data

241. National Pedon Database Summary Layer

name:national-pedon-database-summary-layer reference:https://open.canada.ca/data/en/dataset/6457fad6-b6f5-47a3-9bd1-ad14aea4b9e0 citation: description:The National Pedon Database Summary Layer is a limited, vetted dataset of eight tables containing over a hundred soil properties. Additionally, the National Pedon Database Summary layer is only a subset of the information contained within the National Pedon Database holdings (NPDB)

242. Nuclear Power Plants Database

name:nuclear-power-plants reference:https://github.com/cristianst85/GeoNuclearData citation: description:Database with information about Nuclear Power Plants worldwide

243. The US Forest Service, Forest Health Monitoring, Minnesota

name:forest-health-monitoring-minnesota reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

244. Soil Landscapes of Canada Version

name:soil-landscapes-of-canada reference:https://open.canada.ca/data/en/dataset/4b0ae142-9ff0-4d8f-abf5-36b2b4edd52d citation: description:The “Soil Landscapes of Canada (SLC) Version 2.2” dataset series provides a set of geo-referenced soil areas (polygons) that are linked to attribute data found in the associated Component Table (CMP), Landscape Table (LAT), Carbon Layer Table (CLYR), and Dom/Sub File (DOM_SUB)

245. Fia montana, MT

name:fia-montana reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

246. New York City Airbnb Open Data

name:new-york-city-airbnb-open-data reference:https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data citation: description:Airbnb listings and metrics in NYC, NY, USA (2019)

247. Fia alaska, AK

name:fia-alaska reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

248. The US Forest Service, Forest Health Monitoring, Tennessee

name:forest-health-monitoring-tennessee reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

249. The USA Activity Range Vegetation Improvement dataset

name:activity-range-vegetation-improvement reference:https://data.fs.usda.gov/geodata/edw/datasets.php citation:United States Department of Agriculture - Forest Service. 20210407. Activity Range Vegetation Improvement: S_USA.Activity_RngVegImprove. https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Activity_RngVegImprove.xml. description:The Activity Range Vegetation Improvement depicts the area planned and accomplished areas treated as a part of the Range Vegetation Improvement program of work

250. Restaurant in Baltimore city

name:baltimore-restaurants reference:https://catalog.data.gov/dataset/restaurants-15baa citation: description:List of restaurants on Baltimore City

251. Virgin islands coral taxonomy

name:virgin-islands-coral-taxonomy reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:N/A description:Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

252. Fia maine, ME

name:fia-maine reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

253. Long-Term Soil Productivity (LTSP) Experiment, Fernow experimental Forest, LTREB

name:fernow-soil-productivity reference:http://www.as.wvu.edu/fernow/data.html citation: description:Fernow experimental Forest, LTREB, Soil Productivity, See Data policy

254. Fia new-mexico, NM

name:fia-new-mexico reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

255. WorldClim variables WorldClim version 2 at 5 minutes

name:worldclim-five reference:http://worldclim.org/version2 citation:Fick, S.E. and R.J. Hijmans, 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. description:WorldClim variables at 5 minutes, minimum temperature (°C), maximum temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1), water vapor pressure (kPa), Bioclimatic variables

256. National Nutrient Database for Standard Reference Legacy Release (SR Legacy)

name:usda-mafcl-fooddatacenteral-srlegacy reference:usda-mafcl-fooddatacenteral-srlegacy’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:The data provides a list of nutrient and food component values that are derived from analyses, calculations, and the published literature.

257. Fia guam, GU

name:fia-guam reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

258. Alberta Detailed Soil Survey

name:alberta-detailed-soil-survey reference:https://open.canada.ca/data/en/dataset/9150ad66-73f7-444f-a67c-4be5cf676453 citation: description:The Agricultural Region of Alberta Soil Inventory Database (AGRASID3.0) Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF).

259. Fia texas, TX

name:fia-texas reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

260. The US Forest Service, Forest Health Monitoring, Utah

name:forest-health-monitoring-utah reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

261. DS4C: Data Science for COVID-19 in South Korea

name:coronavirus-south-korea reference:https://www.kaggle.com/kimjihoo/coronavirusdataset citation: description:NeurIPS 2020 Data Science for COVID-19, South Korea

262. The US Forest Service, Forest Health Monitoring, Washington

name:forest-health-monitoring-washington reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

263. Third-order and Upper watershed White Clay Creek and Boulton Run – Climate, Stable Isotopes, Stream Water Chemistry,Precipitation Stable Isotopes (2011-2012)

name:white-clay-creek-boulton-chemistry reference:https://www.hydroshare.org/resource/ff7435cd22d94914ad3a674c40b229e9/ citation:Karwan, D., O. Lazareva, A. Aufdenkampe (2018). Third-order White Clay Creek and Boulton Run - Climate, Stable Isotopes, Stream Water Chemistry (2011-2012), HydroShare, https://doi.org/10.4211/hs.ff7435cd22d94914ad3a674c40b229e9 description:Deuterium and Oxygen-18 measured on stream water samples collected during baseflow, stormflow conditions, time-integrated and bulk precipitation

264. The US Forest Service, Forest Health Monitoring, Alabama

name:forest-health-monitoring-alabama reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

265. Fia new-hampshire, NH

name:fia-new-hampshire reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

266. Virgin Islands National Park: Population Dynamics of Diadema antillarum

name:virgin-islands-coral-diadema-antillarum reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Levitan, D.R., Edmunds, P.J. & Levitan, K.E. Oecologia (2014) 175: 117. https://doi.org/10.1007/s00442-013-2871-9 description:Long-term Coral Reef Community Dynamics, St. John, Virgin Islands National Park, CSUN. http://coralreefs.csun.edu/legal/use-policy/

267. Fia northern-mariana-islands, MP

name:fia-northern-mariana-islands reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

268. Fia wisconsin, WI

name:fia-wisconsin reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

269. Fia rhode-island, RI

name:fia-rhode-island reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

270. Fia delaware, DE

name:fia-delaware reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

271. The US Forest Service, Forest Health Monitoring, Wyoming

name:forest-health-monitoring-wyoming reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

272. fill

name:nlcd-imperviousness-conus reference:fill citation: description:NLCD imperviousness products. Default bounding box is [xmin,ymax,xmax,ymin][-110,50,-100,30]

273. Fia hawaii, HI

name:fia-hawaii reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

274. Virgin Islands National Park: Coral Reef: Juvenile Coral

name:virgin-islands-coral-juvenile reference:http://coralreefs.csun.edu/data/data-catalogue/ citation:Edmunds P. 2016. Virgin Islands National Park: Coral Reef: Juvenile Coral. Environmental Data Initiative. https://doi.org/10.6073/pasta/cd413c7d15f1d73f48def3f8167bf486. Dataset accessed 10/10/2019. description:juvenile scleractinians data, Coral Time-Series Data from St John and St Thomas Islands, http://coralreefs.csun.edu/legal/use-policy/

275. Fia west-virginia, WV

name:fia-west-virginia reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

276. Fia missouri, MO

name:fia-missouri reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

277. Fia connecticut, CT

name:fia-connecticut reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

278. Fia washington, WA

name:fia-washington reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

279. Cervical cancer (Risk Factors) Data Set

name:risk-factors-cervical-cancer reference:http://archive.ics.uci.edu/ml/datasets/Cervical+cancer+%28Risk+Factors%29 citation:Kelwin Fernandes, Jaime S. Cardoso, and Jessica Fernandes. ‘Transfer Learning with Partial Observability Applied to Cervical Cancer Screening.’ Iberian Conference on Pattern Recognition and Image Analysis. Springer International Publishing, 2017. description:This dataset focuses on the prediction of indicators/diagnosis of cervical cancer. The features cover demographic information, habits, and historic medical records.

280. Fernow Experimental Forest daily precipitation

name:fernow-precipitation reference:https://www.fs.usda.gov/rds/archive/catalog/RDS-2011-0014 citation:Edwards, Pamela J.; Wood, Frederica. 2011. Fernow Experimental Forest daily precipitation. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. Data publication updated 19 September 2017. https://doi.org/10.2737/RDS-2011-0014 description:The data publication contains daily watershed-weighted precipitation measured for nine watersheds on the Fernow Experimental Forest from 1951 to 2015.

281. The US Forest Service, Forest Health Monitoring, Missouri

name:forest-health-monitoring-missouri reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

282. Fia nevada, NV

name:fia-nevada reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

283. Portal Project Teaching

name:portal-project-teaching reference:https://figshare.com/articles/Portal_Project_Teaching_Database/1314459 citation: description:The Portal Project Teaching Database is a simplified version of the Portal Project Database designed for teaching

284. USDA Global Branded Food Products Database (Branded Foods)

name:usda-mafcl-fooddatacenteral-brandedfoods reference:usda-mafcl-fooddatacenteral-brandedfoods’s home link. citation:U.S. Department of Agriculture, Agricultural Research Service. FoodData Central, 2019. fdc.nal.usda.gov description:The data is compiled from public-private partnership that provides values for nutrients in branded and private label foods that appear on the product label

285. Fia south-dakota, SD

name:fia-south-dakota reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

286. Fia minnesota, MN

name:fia-minnesota reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

287. Fia new-york, NY

name:fia-new-york reference:https://www.fia.fs.fed.us/ citation:June 20, 2019. Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station description:The Forest Inventory and Analysis (FIA) Program of the U.S.

288. The US Forest Service, Forest Health Monitoring, New Jersey

name:forest-health-monitoring-newjersey reference:https://www.fia.fs.fed.us/tools-data/other_data/index.php citation: description:The USDA Forest Service, Forest Health Monitoring (FHM) is a national program designed to determine the status, changes, and trends in indicators of forest condition on an annual basis.

289. fill

name:nlcd-urban-imperviousness-alaska reference:fill citation:fill description:NLCD_2011_Urban_Descriptor_AK_20200724.img

290. Dissolved organic carbon concentrations in White Clay Creek, Pennsylvania, 1977-2017

name:white-clay-dissolved-carbon reference:https://portal.edirepository.org/nis/mapbrowse?packageid=edi.386.1 citation:Kaplan L. A. 2019. Dissolved organic carbon concentrations in White Clay Creek, Pennsylvania, 1977-2017. Environmental Data Initiative. https://doi.org/10.6073/pasta/60deae3675ff30109bf7a35cceaf719d. Dataset accessed 10/15/2019. description:The data is of dissolved organic carbon concentrations were measured over a period of 4 decades in a 3rd-order reach of White Clay Creek, a stream with a forested riparian zone in the Southeastern Pennsylvania Piedmont

291. U.S. Department of Agriculture’s PLANTS Database

name:usda-agriculture-plants-database reference:https://plants.sc.egov.usda.gov/download.html citation: description:U.S. Department of Agriculture’s PLANTS Database

292. Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference, Release 28

name:usda-mafcl-standard-reference reference:usda-mafcl-standard-reference’s home link. citation:US Department of Agriculture, Agricultural Research Service. 2016. Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference, Release 28 (Slightly revised). Version Current: May 2016. http://www.ars.usda.gov/nea/bhnrc/mafcl description:The dataset contains nutrient data for Standard Reference

APIs Available

Socrata API

Total number of datasets supported : 85,244 out of 213,965

Rdatasets

1. Fair’s Extramarital Affairs Data

name:rdataset-aer-affairs reference:rdataset-aer-affairs’s home link. R package:aer R Dataset:affairs

2. Consumer Price Index in Argentina

name:rdataset-aer-argentinacpi reference:rdataset-aer-argentinacpi’s home link. R package:aer R Dataset:argentinacpi

3. Bank Wages

name:rdataset-aer-bankwages reference:rdataset-aer-bankwages’s home link. R package:aer R Dataset:bankwages

4. Benderly and Zwick Data: Inflation, Growth and Stock Returns

name:rdataset-aer-benderlyzwick reference:rdataset-aer-benderlyzwick’s home link. R package:aer R Dataset:benderlyzwick

5. Bond Yield Data

name:rdataset-aer-bondyield reference:rdataset-aer-bondyield’s home link. R package:aer R Dataset:bondyield

6. CartelStability

name:rdataset-aer-cartelstability reference:rdataset-aer-cartelstability’s home link. R package:aer R Dataset:cartelstability

7. California Test Score Data

name:rdataset-aer-caschools reference:rdataset-aer-caschools’s home link. R package:aer R Dataset:caschools

8. Chinese Real National Income Data

name:rdataset-aer-chinaincome reference:rdataset-aer-chinaincome’s home link. R package:aer R Dataset:chinaincome

9. Cigarette Consumption Data

name:rdataset-aer-cigarettesb reference:rdataset-aer-cigarettesb’s home link. R package:aer R Dataset:cigarettesb

10. Cigarette Consumption Panel Data

name:rdataset-aer-cigarettessw reference:rdataset-aer-cigarettessw’s home link. R package:aer R Dataset:cigarettessw

11. College Distance Data

name:rdataset-aer-collegedistance reference:rdataset-aer-collegedistance’s home link. R package:aer R Dataset:collegedistance

12. Properties of a Fast-Moving Consumer Good

name:rdataset-aer-consumergood reference:rdataset-aer-consumergood’s home link. R package:aer R Dataset:consumergood

13. Determinants of Wages Data (CPS 1985)

name:rdataset-aer-cps1985 reference:rdataset-aer-cps1985’s home link. R package:aer R Dataset:cps1985

14. Determinants of Wages Data (CPS 1988)

name:rdataset-aer-cps1988 reference:rdataset-aer-cps1988’s home link. R package:aer R Dataset:cps1988

15. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssw04 reference:rdataset-aer-cpssw04’s home link. R package:aer R Dataset:cpssw04

16. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssw3 reference:rdataset-aer-cpssw3’s home link. R package:aer R Dataset:cpssw3

17. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssw8 reference:rdataset-aer-cpssw8’s home link. R package:aer R Dataset:cpssw8

18. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssw9204 reference:rdataset-aer-cpssw9204’s home link. R package:aer R Dataset:cpssw9204

19. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssw9298 reference:rdataset-aer-cpssw9298’s home link. R package:aer R Dataset:cpssw9298

20. Stock and Watson CPS Data Sets

name:rdataset-aer-cpssweducation reference:rdataset-aer-cpssweducation’s home link. R package:aer R Dataset:cpssweducation

21. Expenditure and Default Data

name:rdataset-aer-creditcard reference:rdataset-aer-creditcard’s home link. R package:aer R Dataset:creditcard

22. Dow Jones Index Data (Franses)

name:rdataset-aer-djfranses reference:rdataset-aer-djfranses’s home link. R package:aer R Dataset:djfranses

23. Dow Jones Industrial Average (DJIA) index

name:rdataset-aer-djia8012 reference:rdataset-aer-djia8012’s home link. R package:aer R Dataset:djia8012

24. Australian Health Service Utilization Data

name:rdataset-aer-doctorvisits reference:rdataset-aer-doctorvisits’s home link. R package:aer R Dataset:doctorvisits

25. TV and Radio Advertising Expenditures Data

name:rdataset-aer-dutchadvert reference:rdataset-aer-dutchadvert’s home link. R package:aer R Dataset:dutchadvert

26. Dutch Retail Sales Index Data

name:rdataset-aer-dutchsales reference:rdataset-aer-dutchsales’s home link. R package:aer R Dataset:dutchsales

27. Cost Function of Electricity Producers (1955, Nerlove Data)

name:rdataset-aer-electricity1955 reference:rdataset-aer-electricity1955’s home link. R package:aer R Dataset:electricity1955

28. Cost Function of Electricity Producers 1970

name:rdataset-aer-electricity1970 reference:rdataset-aer-electricity1970’s home link. R package:aer R Dataset:electricity1970

29. Number of Equations and Citations for Evolutionary Biology Publications

name:rdataset-aer-equationcitations reference:rdataset-aer-equationcitations’s home link. R package:aer R Dataset:equationcitations

30. Transportation Equipment Manufacturing Data

name:rdataset-aer-equipment reference:rdataset-aer-equipment’s home link. R package:aer R Dataset:equipment

31. European Energy Consumption Data

name:rdataset-aer-euroenergy reference:rdataset-aer-euroenergy’s home link. R package:aer R Dataset:euroenergy

32. US Traffic Fatalities

name:rdataset-aer-fatalities reference:rdataset-aer-fatalities’s home link. R package:aer R Dataset:fatalities

33. Fertility and Women’s Labor Supply

name:rdataset-aer-fertility reference:rdataset-aer-fertility’s home link. R package:aer R Dataset:fertility

34. Fertility and Women’s Labor Supply

name:rdataset-aer-fertility2 reference:rdataset-aer-fertility2’s home link. R package:aer R Dataset:fertility2

35. Price of Frozen Orange Juice

name:rdataset-aer-frozenjuice reference:rdataset-aer-frozenjuice’s home link. R package:aer R Dataset:frozenjuice

36. Unemployment in Germany Data

name:rdataset-aer-germanunemployment reference:rdataset-aer-germanunemployment’s home link. R package:aer R Dataset:germanunemployment

37. Gold and Silver Prices

name:rdataset-aer-goldsilver reference:rdataset-aer-goldsilver’s home link. R package:aer R Dataset:goldsilver

38. Determinants of Economic Growth

name:rdataset-aer-growthdj reference:rdataset-aer-growthdj’s home link. R package:aer R Dataset:growthdj

39. Determinants of Economic Growth

name:rdataset-aer-growthsw reference:rdataset-aer-growthsw’s home link. R package:aer R Dataset:growthsw

40. Grunfeld’s Investment Data

name:rdataset-aer-grunfeld reference:rdataset-aer-grunfeld’s home link. R package:aer R Dataset:grunfeld

41. German Socio-Economic Panel 1994-2002

name:rdataset-aer-gsoep9402 reference:rdataset-aer-gsoep9402’s home link. R package:aer R Dataset:gsoep9402

42. US General Social Survey 1974-2002

name:rdataset-aer-gss7402 reference:rdataset-aer-gss7402’s home link. R package:aer R Dataset:gss7402

43. More Guns, Less Crime?

name:rdataset-aer-guns reference:rdataset-aer-guns’s home link. R package:aer R Dataset:guns

44. Medical Expenditure Panel Survey Data

name:rdataset-aer-healthinsurance reference:rdataset-aer-healthinsurance’s home link. R package:aer R Dataset:healthinsurance

45. Home Mortgage Disclosure Act Data

name:rdataset-aer-hmda reference:rdataset-aer-hmda’s home link. R package:aer R Dataset:hmda

46. House Prices in the City of Windsor, Canada

name:rdataset-aer-houseprices reference:rdataset-aer-houseprices’s home link. R package:aer R Dataset:houseprices

47. Economics Journal Subscription Data

name:rdataset-aer-journals reference:rdataset-aer-journals’s home link. R package:aer R Dataset:journals

48. Klein Model I

name:rdataset-aer-kleini reference:rdataset-aer-kleini’s home link. R package:aer R Dataset:kleini

49. Longley’s Regression Data

name:rdataset-aer-longley reference:rdataset-aer-longley’s home link. R package:aer R Dataset:longley

50. Manufacturing Costs Data

name:rdataset-aer-manufactcosts reference:rdataset-aer-manufactcosts’s home link. R package:aer R Dataset:manufactcosts

51. DEM/USD Exchange Rate Returns

name:rdataset-aer-markdollar reference:rdataset-aer-markdollar’s home link. R package:aer R Dataset:markdollar

52. DEM/GBP Exchange Rate Returns

name:rdataset-aer-markpound reference:rdataset-aer-markpound’s home link. R package:aer R Dataset:markpound

53. Massachusetts Test Score Data

name:rdataset-aer-maschools reference:rdataset-aer-maschools’s home link. R package:aer R Dataset:maschools

54. Medicaid Utilization Data

name:rdataset-aer-medicaid1986 reference:rdataset-aer-medicaid1986’s home link. R package:aer R Dataset:medicaid1986

55. Fixed versus Adjustable Mortgages

name:rdataset-aer-mortgage reference:rdataset-aer-mortgage’s home link. R package:aer R Dataset:mortgage

56. Motor Cycles in The Netherlands

name:rdataset-aer-motorcycles reference:rdataset-aer-motorcycles’s home link. R package:aer R Dataset:motorcycles

57. Motor Cycles in The Netherlands

name:rdataset-aer-motorcycles2 reference:rdataset-aer-motorcycles2’s home link. R package:aer R Dataset:motorcycles2

58. MSCI Switzerland Index

name:rdataset-aer-msciswitzerland reference:rdataset-aer-msciswitzerland’s home link. R package:aer R Dataset:msciswitzerland

59. Municipal Expenditure Data

name:rdataset-aer-municipalities reference:rdataset-aer-municipalities’s home link. R package:aer R Dataset:municipalities

60. Determinants of Murder Rates in the United States

name:rdataset-aer-murderrates reference:rdataset-aer-murderrates’s home link. R package:aer R Dataset:murderrates

61. Natural Gas Data

name:rdataset-aer-naturalgas reference:rdataset-aer-naturalgas’s home link. R package:aer R Dataset:naturalgas

62. Demand for Medical Care in NMES 1988

name:rdataset-aer-nmes1988 reference:rdataset-aer-nmes1988’s home link. R package:aer R Dataset:nmes1988

63. Daily NYSE Composite Index

name:rdataset-aer-nysesw reference:rdataset-aer-nysesw’s home link. R package:aer R Dataset:nysesw

64. Gasoline Consumption Data

name:rdataset-aer-oecdgas reference:rdataset-aer-oecdgas’s home link. R package:aer R Dataset:oecdgas

65. OECD Macroeconomic Data

name:rdataset-aer-oecdgrowth reference:rdataset-aer-oecdgrowth’s home link. R package:aer R Dataset:oecdgrowth

66. Television Rights for Olympic Games

name:rdataset-aer-olympictv reference:rdataset-aer-olympictv’s home link. R package:aer R Dataset:olympictv

67. Orange County Employment

name:rdataset-aer-orangecounty reference:rdataset-aer-orangecounty’s home link. R package:aer R Dataset:orangecounty

68. Parade Magazine 2005 Earnings Data

name:rdataset-aer-parade2005 reference:rdataset-aer-parade2005’s home link. R package:aer R Dataset:parade2005

69. Black and White Pepper Prices

name:rdataset-aer-pepperprice reference:rdataset-aer-pepperprice’s home link. R package:aer R Dataset:pepperprice

70. Doctoral Publications

name:rdataset-aer-phdpublications reference:rdataset-aer-phdpublications’s home link. R package:aer R Dataset:phdpublications

71. Program Effectiveness Data

name:rdataset-aer-programeffectiveness reference:rdataset-aer-programeffectiveness’s home link. R package:aer R Dataset:programeffectiveness

72. Labor Force Participation Data

name:rdataset-aer-psid1976 reference:rdataset-aer-psid1976’s home link. R package:aer R Dataset:psid1976

73. PSID Earnings Data 1982

name:rdataset-aer-psid1982 reference:rdataset-aer-psid1982’s home link. R package:aer R Dataset:psid1982

74. PSID Earnings Panel Data (1976-1982)

name:rdataset-aer-psid7682 reference:rdataset-aer-psid7682’s home link. R package:aer R Dataset:psid7682

75. Recreation Demand Data

name:rdataset-aer-recreationdemand reference:rdataset-aer-recreationdemand’s home link. R package:aer R Dataset:recreationdemand

76. Are Emily and Greg More Employable Than Lakisha and Jamal?

name:rdataset-aer-resumenames reference:rdataset-aer-resumenames’s home link. R package:aer R Dataset:resumenames

77. Ship Accidents

name:rdataset-aer-shipaccidents reference:rdataset-aer-shipaccidents’s home link. R package:aer R Dataset:shipaccidents

78. SIC33 Production Data

name:rdataset-aer-sic33 reference:rdataset-aer-sic33’s home link. R package:aer R Dataset:sic33

79. Do Workplace Smoking Bans Reduce Smoking?

name:rdataset-aer-smokeban reference:rdataset-aer-smokeban’s home link. R package:aer R Dataset:smokeban

80. Endowment Effect for Sports Cards

name:rdataset-aer-sportscards reference:rdataset-aer-sportscards’s home link. R package:aer R Dataset:sportscards

81. Project STAR: Student-Teacher Achievement Ratio

name:rdataset-aer-star reference:rdataset-aer-star’s home link. R package:aer R Dataset:star

82. Strike Durations

name:rdataset-aer-strikeduration reference:rdataset-aer-strikeduration’s home link. R package:aer R Dataset:strikeduration

83. Swiss Labor Market Participation Data

name:rdataset-aer-swisslabor reference:rdataset-aer-swisslabor’s home link. R package:aer R Dataset:swisslabor

84. Impact of Beauty on Instructor’s Teaching Ratings

name:rdataset-aer-teachingratings reference:rdataset-aer-teachingratings’s home link. R package:aer R Dataset:teachingratings

85. Technological Change Data

name:rdataset-aer-techchange reference:rdataset-aer-techchange’s home link. R package:aer R Dataset:techchange

86. Trade Credit and the Money Market

name:rdataset-aer-tradecredit reference:rdataset-aer-tradecredit’s home link. R package:aer R Dataset:tradecredit

87. Travel Mode Choice Data

name:rdataset-aer-travelmode reference:rdataset-aer-travelmode’s home link. R package:aer R Dataset:travelmode

88. UK Manufacturing Inflation Data

name:rdataset-aer-ukinflation reference:rdataset-aer-ukinflation’s home link. R package:aer R Dataset:ukinflation

89. Consumption of Non-Durables in the UK

name:rdataset-aer-uknondurables reference:rdataset-aer-uknondurables’s home link. R package:aer R Dataset:uknondurables

90. Cost Data for US Airlines

name:rdataset-aer-usairlines reference:rdataset-aer-usairlines’s home link. R package:aer R Dataset:usairlines

91. US Consumption Data (1940-1950)

name:rdataset-aer-usconsump1950 reference:rdataset-aer-usconsump1950’s home link. R package:aer R Dataset:usconsump1950

92. US Consumption Data (1970-1979)

name:rdataset-aer-usconsump1979 reference:rdataset-aer-usconsump1979’s home link. R package:aer R Dataset:usconsump1979

93. US Consumption Data (1950-1993)

name:rdataset-aer-usconsump1993 reference:rdataset-aer-usconsump1993’s home link. R package:aer R Dataset:usconsump1993

94. US Crudes Data

name:rdataset-aer-uscrudes reference:rdataset-aer-uscrudes’s home link. R package:aer R Dataset:uscrudes

95. US Gasoline Market Data (1950-1987, Baltagi)

name:rdataset-aer-usgasb reference:rdataset-aer-usgasb’s home link. R package:aer R Dataset:usgasb

96. US Gasoline Market Data (1960-1995, Greene)

name:rdataset-aer-usgasg reference:rdataset-aer-usgasg’s home link. R package:aer R Dataset:usgasg

97. US Investment Data

name:rdataset-aer-usinvest reference:rdataset-aer-usinvest’s home link. R package:aer R Dataset:usinvest

98. US Macroeconomic Data (1959-1995, Baltagi)

name:rdataset-aer-usmacrob reference:rdataset-aer-usmacrob’s home link. R package:aer R Dataset:usmacrob

99. US Macroeconomic Data (1950-2000, Greene)

name:rdataset-aer-usmacrog reference:rdataset-aer-usmacrog’s home link. R package:aer R Dataset:usmacrog

100. US Macroeconomic Data (1957-2005, Stock & Watson)

name:rdataset-aer-usmacrosw reference:rdataset-aer-usmacrosw’s home link. R package:aer R Dataset:usmacrosw

101. Monthly US Macroeconomic Data (1947-2004, Stock & Watson)

name:rdataset-aer-usmacroswm reference:rdataset-aer-usmacroswm’s home link. R package:aer R Dataset:usmacroswm

102. Quarterly US Macroeconomic Data (1947-2004, Stock & Watson)

name:rdataset-aer-usmacroswq reference:rdataset-aer-usmacroswq’s home link. R package:aer R Dataset:usmacroswq

103. USMoney

name:rdataset-aer-usmoney reference:rdataset-aer-usmoney’s home link. R package:aer R Dataset:usmoney

104. Index of US Industrial Production

name:rdataset-aer-usprodindex reference:rdataset-aer-usprodindex’s home link. R package:aer R Dataset:usprodindex

105. Effects of Mandatory Seat Belt Laws in the US

name:rdataset-aer-usseatbelts reference:rdataset-aer-usseatbelts’s home link. R package:aer R Dataset:usseatbelts

106. Monthly US Stock Returns (1931-2002, Stock & Watson)

name:rdataset-aer-usstockssw reference:rdataset-aer-usstockssw’s home link. R package:aer R Dataset:usstockssw

107. Artificial Weak Instrument Data

name:rdataset-aer-weakinstrument reference:rdataset-aer-weakinstrument’s home link. R package:aer R Dataset:weakinstrument

108. ashkenazi

name:rdataset-asaur-ashkenazi reference:rdataset-asaur-ashkenazi’s home link. R package:asaur R Dataset:ashkenazi

109. Channing House Data

name:rdataset-asaur-channinghouse reference:rdataset-asaur-channinghouse’s home link. R package:asaur R Dataset:channinghouse

110. gasticXelox

name:rdataset-asaur-gastricxelox reference:rdataset-asaur-gastricxelox’s home link. R package:asaur R Dataset:gastricxelox

111. hepatoCellular

name:rdataset-asaur-hepatocellular reference:rdataset-asaur-hepatocellular’s home link. R package:asaur R Dataset:hepatocellular

112. pancreatic

name:rdataset-asaur-pancreatic reference:rdataset-asaur-pancreatic’s home link. R package:asaur R Dataset:pancreatic

113. pancreatic2

name:rdataset-asaur-pancreatic2 reference:rdataset-asaur-pancreatic2’s home link. R package:asaur R Dataset:pancreatic2

114. pharmacoSmoking

name:rdataset-asaur-pharmacosmoking reference:rdataset-asaur-pharmacosmoking’s home link. R package:asaur R Dataset:pharmacosmoking

115. prostateSurvival

name:rdataset-asaur-prostatesurvival reference:rdataset-asaur-prostatesurvival’s home link. R package:asaur R Dataset:prostatesurvival

116. Monthly Excess Returns

name:rdataset-boot-acme reference:rdataset-boot-acme’s home link. R package:boot R Dataset:acme

117. Delay in AIDS Reporting in England and Wales

name:rdataset-boot-aids reference:rdataset-boot-aids’s home link. R package:boot R Dataset:aids

118. Failures of Air-conditioning Equipment

name:rdataset-boot-aircondit reference:rdataset-boot-aircondit’s home link. R package:boot R Dataset:aircondit

119. Failures of Air-conditioning Equipment

name:rdataset-boot-aircondit7 reference:rdataset-boot-aircondit7’s home link. R package:boot R Dataset:aircondit7

120. Car Speeding and Warning Signs

name:rdataset-boot-amis reference:rdataset-boot-amis’s home link. R package:boot R Dataset:amis

121. Remission Times for Acute Myelogenous Leukaemia

name:rdataset-boot-aml reference:rdataset-boot-aml’s home link. R package:boot R Dataset:aml

122. Beaver Body Temperature Data

name:rdataset-boot-beaver reference:rdataset-boot-beaver’s home link. R package:boot R Dataset:beaver

123. Population of U.S. Cities

name:rdataset-boot-bigcity reference:rdataset-boot-bigcity’s home link. R package:boot R Dataset:bigcity

124. Spatial Location of Bramble Canes

name:rdataset-boot-brambles reference:rdataset-boot-brambles’s home link. R package:boot R Dataset:brambles

125. Smoking Deaths Among Doctors

name:rdataset-boot-breslow reference:rdataset-boot-breslow’s home link. R package:boot R Dataset:breslow

126. Calcium Uptake Data

name:rdataset-boot-calcium reference:rdataset-boot-calcium’s home link. R package:boot R Dataset:calcium

127. Sugar-cane Disease Data

name:rdataset-boot-cane reference:rdataset-boot-cane’s home link. R package:boot R Dataset:cane

128. Simulated Manufacturing Process Data

name:rdataset-boot-capability reference:rdataset-boot-capability’s home link. R package:boot R Dataset:capability

129. Weight Data for Domestic Cats

name:rdataset-boot-catsm reference:rdataset-boot-catsm’s home link. R package:boot R Dataset:catsm

130. Position of Muscle Caveolae

name:rdataset-boot-cav reference:rdataset-boot-cav’s home link. R package:boot R Dataset:cav

131. CD4 Counts for HIV-Positive Patients

name:rdataset-boot-cd4 reference:rdataset-boot-cd4’s home link. R package:boot R Dataset:cd4

132. Channing House Data

name:rdataset-boot-channing reference:rdataset-boot-channing’s home link. R package:boot R Dataset:channing

133. Population of U.S. Cities

name:rdataset-boot-city reference:rdataset-boot-city’s home link. R package:boot R Dataset:city

134. Genetic Links to Left-handedness

name:rdataset-boot-claridge reference:rdataset-boot-claridge’s home link. R package:boot R Dataset:claridge

135. Number of Flaws in Cloth

name:rdataset-boot-cloth reference:rdataset-boot-cloth’s home link. R package:boot R Dataset:cloth

136. Carbon Monoxide Transfer

name:rdataset-boot-co.transfer reference:rdataset-boot-co.transfer’s home link. R package:boot R Dataset:co.transfer

137. Dates of Coal Mining Disasters

name:rdataset-boot-coal reference:rdataset-boot-coal’s home link. R package:boot R Dataset:coal

138. Darwin’s Plant Height Differences

name:rdataset-boot-darwin reference:rdataset-boot-darwin’s home link. R package:boot R Dataset:darwin

139. Cardiac Data for Domestic Dogs

name:rdataset-boot-dogs reference:rdataset-boot-dogs’s home link. R package:boot R Dataset:dogs

140. Incidence of Down’s Syndrome in British Columbia

name:rdataset-boot-downs.bc reference:rdataset-boot-downs.bc’s home link. R package:boot R Dataset:downs.bc

141. Behavioral and Plumage Characteristics of Hybrid Ducks

name:rdataset-boot-ducks reference:rdataset-boot-ducks’s home link. R package:boot R Dataset:ducks

142. Counts of Balsam-fir Seedlings

name:rdataset-boot-fir reference:rdataset-boot-fir’s home link. R package:boot R Dataset:fir

143. Head Dimensions in Brothers

name:rdataset-boot-frets reference:rdataset-boot-frets’s home link. R package:boot R Dataset:frets

144. Acceleration Due to Gravity

name:rdataset-boot-grav reference:rdataset-boot-grav’s home link. R package:boot R Dataset:grav

145. Acceleration Due to Gravity

name:rdataset-boot-gravity reference:rdataset-boot-gravity’s home link. R package:boot R Dataset:gravity

146. Failure Time of PET Film

name:rdataset-boot-hirose reference:rdataset-boot-hirose’s home link. R package:boot R Dataset:hirose

147. Jura Quartzite Azimuths on Islay

name:rdataset-boot-islay reference:rdataset-boot-islay’s home link. R package:boot R Dataset:islay

148. Average Heights of the Rio Negro river at Manaus

name:rdataset-boot-manaus reference:rdataset-boot-manaus’s home link. R package:boot R Dataset:manaus

149. Survival from Malignant Melanoma

name:rdataset-boot-melanoma reference:rdataset-boot-melanoma’s home link. R package:boot R Dataset:melanoma

150. Data from a Simulated Motorcycle Accident

name:rdataset-boot-motor reference:rdataset-boot-motor’s home link. R package:boot R Dataset:motor

151. Neurophysiological Point Process Data

name:rdataset-boot-neuro reference:rdataset-boot-neuro’s home link. R package:boot R Dataset:neuro

152. Toxicity of Nitrofen in Aquatic Systems

name:rdataset-boot-nitrofen reference:rdataset-boot-nitrofen’s home link. R package:boot R Dataset:nitrofen

153. Nodal Involvement in Prostate Cancer

name:rdataset-boot-nodal reference:rdataset-boot-nodal’s home link. R package:boot R Dataset:nodal

154. Nuclear Power Station Construction Data

name:rdataset-boot-nuclear reference:rdataset-boot-nuclear’s home link. R package:boot R Dataset:nuclear

155. Neurotransmission in Guinea Pig Brains

name:rdataset-boot-paulsen reference:rdataset-boot-paulsen’s home link. R package:boot R Dataset:paulsen

156. Animal Survival Times

name:rdataset-boot-poisons reference:rdataset-boot-poisons’s home link. R package:boot R Dataset:poisons

157. Pole Positions of New Caledonian Laterites

name:rdataset-boot-polar reference:rdataset-boot-polar’s home link. R package:boot R Dataset:polar

158. Cancer Remission and Cell Activity

name:rdataset-boot-remission reference:rdataset-boot-remission’s home link. R package:boot R Dataset:remission

159. Water Salinity and River Discharge

name:rdataset-boot-salinity reference:rdataset-boot-salinity’s home link. R package:boot R Dataset:salinity

160. Survival of Rats after Radiation Doses

name:rdataset-boot-survival reference:rdataset-boot-survival’s home link. R package:boot R Dataset:survival

161. Tau Particle Decay Modes

name:rdataset-boot-tau reference:rdataset-boot-tau’s home link. R package:boot R Dataset:tau

162. Tuna Sighting Data

name:rdataset-boot-tuna reference:rdataset-boot-tuna’s home link. R package:boot R Dataset:tuna

163. Urine Analysis Data

name:rdataset-boot-urine reference:rdataset-boot-urine’s home link. R package:boot R Dataset:urine

164. Australian Relative Wool Prices

name:rdataset-boot-wool reference:rdataset-boot-wool’s home link. R package:boot R Dataset:wool

165. Experimenter Expectations

name:rdataset-cardata-adler reference:rdataset-cardata-adler’s home link. R package:cardata R Dataset:adler

166. American Math Society Survey Data

name:rdataset-cardata-amssurvey reference:rdataset-cardata-amssurvey’s home link. R package:cardata R Dataset:amssurvey

167. Moral Integration of American Cities

name:rdataset-cardata-angell reference:rdataset-cardata-angell’s home link. R package:cardata R Dataset:angell

168. U. S. State Public-School Expenditures

name:rdataset-cardata-anscombe reference:rdataset-cardata-anscombe’s home link. R package:cardata R Dataset:anscombe

169. Arrests for Marijuana Possession

name:rdataset-cardata-arrests reference:rdataset-cardata-arrests’s home link. R package:cardata R Dataset:arrests

170. Methods of Teaching Reading Comprehension

name:rdataset-cardata-baumann reference:rdataset-cardata-baumann’s home link. R package:cardata R Dataset:baumann

171. British Election Panel Study

name:rdataset-cardata-beps reference:rdataset-cardata-beps’s home link. R package:cardata R Dataset:beps

172. Canadian Women’s Labour-Force Participation

name:rdataset-cardata-bfox reference:rdataset-cardata-bfox’s home link. R package:cardata R Dataset:bfox

173. Exercise Histories of Eating-Disordered and Control Subjects

name:rdataset-cardata-blackmore reference:rdataset-cardata-blackmore’s home link. R package:cardata R Dataset:blackmore

174. Fraudulent Data on IQs of Twins Raised Apart

name:rdataset-cardata-burt reference:rdataset-cardata-burt’s home link. R package:cardata R Dataset:burt

175. Canadian Population Data

name:rdataset-cardata-canpop reference:rdataset-cardata-canpop’s home link. R package:cardata R Dataset:canpop

176. 2011 Canadian National Election Study, With Attitude Toward Abortion

name:rdataset-cardata-ces11 reference:rdataset-cardata-ces11’s home link. R package:cardata R Dataset:ces11

177. Voting Intentions in the 1988 Chilean Plebiscite

name:rdataset-cardata-chile reference:rdataset-cardata-chile’s home link. R package:cardata R Dataset:chile

178. The 1907 Romanian Peasant Rebellion

name:rdataset-cardata-chirot reference:rdataset-cardata-chirot’s home link. R package:cardata R Dataset:chirot

179. Cowles and Davis’s Data on Volunteering

name:rdataset-cardata-cowles reference:rdataset-cardata-cowles’s home link. R package:cardata R Dataset:cowles

180. Self-Reports of Height and Weight

name:rdataset-cardata-davis reference:rdataset-cardata-davis’s home link. R package:cardata R Dataset:davis

181. Davis’s Data on Drive for Thinness

name:rdataset-cardata-davisthin reference:rdataset-cardata-davisthin’s home link. R package:cardata R Dataset:davisthin

182. Minnesota Wolf Depredation Data

name:rdataset-cardata-depredations reference:rdataset-cardata-depredations’s home link. R package:cardata R Dataset:depredations

183. Duncan’s Occupational Prestige Data

name:rdataset-cardata-duncan reference:rdataset-cardata-duncan’s home link. R package:cardata R Dataset:duncan

184. The 1980 U.S. Census Undercount

name:rdataset-cardata-ericksen reference:rdataset-cardata-ericksen’s home link. R package:cardata R Dataset:ericksen

185. Florida County Voting

name:rdataset-cardata-florida reference:rdataset-cardata-florida’s home link. R package:cardata R Dataset:florida

186. Crowding and Crime in U. S. Metropolitan Areas

name:rdataset-cardata-freedman reference:rdataset-cardata-freedman’s home link. R package:cardata R Dataset:freedman

187. Format Effects on Recall

name:rdataset-cardata-friendly reference:rdataset-cardata-friendly’s home link. R package:cardata R Dataset:friendly

188. Data on Depression

name:rdataset-cardata-ginzberg reference:rdataset-cardata-ginzberg’s home link. R package:cardata R Dataset:ginzberg

189. Refugee Appeals

name:rdataset-cardata-greene reference:rdataset-cardata-greene’s home link. R package:cardata R Dataset:greene

190. Data from the General Social Survey (GSS) from the National Opinion Research Center of the University of Chicago.

name:rdataset-cardata-gssvocab reference:rdataset-cardata-gssvocab’s home link. R package:cardata R Dataset:gssvocab

191. Anonymity and Cooperation

name:rdataset-cardata-guyer reference:rdataset-cardata-guyer’s home link. R package:cardata R Dataset:guyer

192. Canadian Crime-Rates Time Series

name:rdataset-cardata-hartnagel reference:rdataset-cardata-hartnagel’s home link. R package:cardata R Dataset:hartnagel

193. Highway Accidents

name:rdataset-cardata-highway1 reference:rdataset-cardata-highway1’s home link. R package:cardata R Dataset:highway1

194. Treatment of Migraine Headaches

name:rdataset-cardata-kosteckidillon reference:rdataset-cardata-kosteckidillon’s home link. R package:cardata R Dataset:kosteckidillon

195. Data on Infant-Mortality

name:rdataset-cardata-leinhardt reference:rdataset-cardata-leinhardt’s home link. R package:cardata R Dataset:leinhardt

196. Cancer drug data use to provide an example of the use of the skew power distributions.

name:rdataset-cardata-lobd reference:rdataset-cardata-lobd’s home link. R package:cardata R Dataset:lobd

197. Contrived Collinear Data

name:rdataset-cardata-mandel reference:rdataset-cardata-mandel’s home link. R package:cardata R Dataset:mandel

198. Canadian Interprovincial Migration Data

name:rdataset-cardata-migration reference:rdataset-cardata-migration’s home link. R package:cardata R Dataset:migration

199. Status, Authoritarianism, and Conformity

name:rdataset-cardata-moore reference:rdataset-cardata-moore’s home link. R package:cardata R Dataset:moore

200. Minneapolis Demographic Data 2015, by Neighborhood

name:rdataset-cardata-mplsdemo reference:rdataset-cardata-mplsdemo’s home link. R package:cardata R Dataset:mplsdemo

201. Minneapolis Police Department 2017 Stop Data

name:rdataset-cardata-mplsstops reference:rdataset-cardata-mplsstops’s home link. R package:cardata R Dataset:mplsstops

202. U.S. Women’s Labor-Force Participation

name:rdataset-cardata-mroz reference:rdataset-cardata-mroz’s home link. R package:cardata R Dataset:mroz

203. O’Brien and Kaiser’s Repeated-Measures Data

name:rdataset-cardata-obrienkaiser reference:rdataset-cardata-obrienkaiser’s home link. R package:cardata R Dataset:obrienkaiser

204. O’Brien and Kaiser’s Repeated-Measures Data in “Long” Format

name:rdataset-cardata-obrienkaiserlong reference:rdataset-cardata-obrienkaiserlong’s home link. R package:cardata R Dataset:obrienkaiserlong

205. Interlocking Directorates Among Major Canadian Firms

name:rdataset-cardata-ornstein reference:rdataset-cardata-ornstein’s home link. R package:cardata R Dataset:ornstein

206. Chemical Composition of Pottery

name:rdataset-cardata-pottery reference:rdataset-cardata-pottery’s home link. R package:cardata R Dataset:pottery

207. Prestige of Canadian Occupations

name:rdataset-cardata-prestige reference:rdataset-cardata-prestige’s home link. R package:cardata R Dataset:prestige

208. Four Regression Datasets

name:rdataset-cardata-quartet reference:rdataset-cardata-quartet’s home link. R package:cardata R Dataset:quartet

209. Fertility and Contraception

name:rdataset-cardata-robey reference:rdataset-cardata-robey’s home link. R package:cardata R Dataset:robey

210. Rossi et al.’s Criminal Recidivism Data

name:rdataset-cardata-rossi reference:rdataset-cardata-rossi’s home link. R package:cardata R Dataset:rossi

211. Agricultural Production in Mazulu Village

name:rdataset-cardata-sahlins reference:rdataset-cardata-sahlins’s home link. R package:cardata R Dataset:sahlins

212. Salaries for Professors

name:rdataset-cardata-salaries reference:rdataset-cardata-salaries’s home link. R package:cardata R Dataset:salaries

213. Survey of Labour and Income Dynamics

name:rdataset-cardata-slid reference:rdataset-cardata-slid’s home link. R package:cardata R Dataset:slid

214. Soil Compositions of Physical and Chemical Characteristics

name:rdataset-cardata-soils reference:rdataset-cardata-soils’s home link. R package:cardata R Dataset:soils

215. Education and Related Statistics for the U.S. States

name:rdataset-cardata-states reference:rdataset-cardata-states’s home link. R package:cardata R Dataset:states

216. Survival of Passengers on the Titanic

name:rdataset-cardata-titanicsurvival reference:rdataset-cardata-titanicsurvival’s home link. R package:cardata R Dataset:titanicsurvival

217. Transaction data

name:rdataset-cardata-transact reference:rdataset-cardata-transact’s home link. R package:cardata R Dataset:transact

218. National Statistics from the United Nations, Mostly From 2009-2011

name:rdataset-cardata-un reference:rdataset-cardata-un’s home link. R package:cardata R Dataset:un

219. United Nations Social Indicators Data 1998]

name:rdataset-cardata-un98 reference:rdataset-cardata-un98’s home link. R package:cardata R Dataset:un98

220. Population of the United States

name:rdataset-cardata-uspop reference:rdataset-cardata-uspop’s home link. R package:cardata R Dataset:uspop

221. Vocabulary and Education

name:rdataset-cardata-vocab reference:rdataset-cardata-vocab’s home link. R package:cardata R Dataset:vocab

222. Weight Loss Data

name:rdataset-cardata-weightloss reference:rdataset-cardata-weightloss’s home link. R package:cardata R Dataset:weightloss

223. Well Switching in Bangladesh

name:rdataset-cardata-wells reference:rdataset-cardata-wells’s home link. R package:cardata R Dataset:wells

224. Canadian Women’s Labour-Force Participation

name:rdataset-cardata-womenlf reference:rdataset-cardata-womenlf’s home link. R package:cardata R Dataset:womenlf

225. Post-Coma Recovery of IQ

name:rdataset-cardata-wong reference:rdataset-cardata-wong’s home link. R package:cardata R Dataset:wong

226. Wool data

name:rdataset-cardata-wool reference:rdataset-cardata-wool’s home link. R package:cardata R Dataset:wool

227. World Values Surveys

name:rdataset-cardata-wvs reference:rdataset-cardata-wvs’s home link. R package:cardata R Dataset:wvs

228. Data on abortion legalization and sexually transmitted infections

name:rdataset-causaldata-abortion reference:rdataset-causaldata-abortion’s home link. R package:causaldata R Dataset:abortion

229. Data from a survey of internet-mediated sex workers

name:rdataset-causaldata-adult_services reference:rdataset-causaldata-adult_services’s home link. R package:causaldata R Dataset:adult_services

230. Automobile data from Stata

name:rdataset-causaldata-auto reference:rdataset-causaldata-auto’s home link. R package:causaldata R Dataset:auto

231. Data on avocado sales

name:rdataset-causaldata-avocado reference:rdataset-causaldata-avocado’s home link. R package:causaldata R Dataset:avocado

232. Data from “Black Politicians are More Intrinsically Motivated to Advance Blacks’ Interests”

name:rdataset-causaldata-black_politicians reference:rdataset-causaldata-black_politicians’s home link. R package:causaldata R Dataset:black_politicians

233. Data on castle-doctrine statutes and violent crime

name:rdataset-causaldata-castle reference:rdataset-causaldata-castle’s home link. R package:causaldata R Dataset:castle

234. Data from Card (1995) to estimate the effect of college education on earnings

name:rdataset-causaldata-close_college reference:rdataset-causaldata-close_college’s home link. R package:causaldata R Dataset:close_college

235. A close-elections regression discontinuity study from Lee, Moretti, and Butler (2004)

name:rdataset-causaldata-close_elections_lmb reference:rdataset-causaldata-close_elections_lmb’s home link. R package:causaldata R Dataset:close_elections_lmb

236. Observational counterpart to nsw_mixtape data

name:rdataset-causaldata-cps_mixtape reference:rdataset-causaldata-cps_mixtape’s home link. R package:causaldata R Dataset:cps_mixtape

237. Data on Taiwanese Credit Card Holders

name:rdataset-causaldata-credit_cards reference:rdataset-causaldata-credit_cards’s home link. R package:causaldata R Dataset:credit_cards

238. Gapminder data

name:rdataset-causaldata-gapminder reference:rdataset-causaldata-gapminder’s home link. R package:causaldata R Dataset:gapminder

239. Google Stock Data

name:rdataset-causaldata-google_stock reference:rdataset-causaldata-google_stock’s home link. R package:causaldata R Dataset:google_stock

240. Data from “Government Transfers and Political Support”

name:rdataset-causaldata-gov_transfers reference:rdataset-causaldata-gov_transfers’s home link. R package:causaldata R Dataset:gov_transfers

241. Data from “Government Transfers and Political Support” for Density Tests

name:rdataset-causaldata-gov_transfers_density reference:rdataset-causaldata-gov_transfers_density’s home link. R package:causaldata R Dataset:gov_transfers_density

242. Data from a fictional randomized heart transplant study

name:rdataset-causaldata-greek_data reference:rdataset-causaldata-greek_data’s home link. R package:causaldata R Dataset:greek_data

243. Data from “How do Mortgage Subsidies Affect Home Ownership? Evidence from the Mid-Century GI Bills”

name:rdataset-causaldata-mortgages reference:rdataset-causaldata-mortgages’s home link. R package:causaldata R Dataset:mortgages

244. U.S. Women’s Labor-Force Participation

name:rdataset-causaldata-mroz reference:rdataset-causaldata-mroz’s home link. R package:causaldata R Dataset:mroz

245. National Health and Nutrition Examination Survey Data I Epidemiologic Follow-up Study

name:rdataset-causaldata-nhefs reference:rdataset-causaldata-nhefs’s home link. R package:causaldata R Dataset:nhefs

246. NHEFS Codebook

name:rdataset-causaldata-nhefs_codebook reference:rdataset-causaldata-nhefs_codebook’s home link. R package:causaldata R Dataset:nhefs_codebook

247. Complete-Data National Health and Nutrition Examination Survey Data I Epidemiologic Follow-up Study

name:rdataset-causaldata-nhefs_complete reference:rdataset-causaldata-nhefs_complete’s home link. R package:causaldata R Dataset:nhefs_complete

248. Data from the National Supported Work Demonstration (NSW) job-training program

name:rdataset-causaldata-nsw_mixtape reference:rdataset-causaldata-nsw_mixtape’s home link. R package:causaldata R Dataset:nsw_mixtape

249. Organ Donation Data

name:rdataset-causaldata-organ_donations reference:rdataset-causaldata-organ_donations’s home link. R package:causaldata R Dataset:organ_donations

250. Data on Restaurant Inspections

name:rdataset-causaldata-restaurant_inspections reference:rdataset-causaldata-restaurant_inspections’s home link. R package:causaldata R Dataset:restaurant_inspections

251. A simple simulated data set for calculating p-values

name:rdataset-causaldata-ri reference:rdataset-causaldata-ri’s home link. R package:causaldata R Dataset:ri

252. Earnings and Loan Repayment in US Four-Year Colleges

name:rdataset-causaldata-scorecard reference:rdataset-causaldata-scorecard’s home link. R package:causaldata R Dataset:scorecard

253. Data from John Snow’s 1855 study of the cause of cholera

name:rdataset-causaldata-snow reference:rdataset-causaldata-snow’s home link. R package:causaldata R Dataset:snow

254. Data from “Social Networks and the Decision to Insure”

name:rdataset-causaldata-social_insure reference:rdataset-causaldata-social_insure’s home link. R package:causaldata R Dataset:social_insure

255. Data on prison capacity expansion in Texas

name:rdataset-causaldata-texas reference:rdataset-causaldata-texas’s home link. R package:causaldata R Dataset:texas

256. Data from HIV information experiment in Thornton (2008)

name:rdataset-causaldata-thornton_hiv reference:rdataset-causaldata-thornton_hiv’s home link. R package:causaldata R Dataset:thornton_hiv

257. Data from the sinking of the Titanic

name:rdataset-causaldata-titanic reference:rdataset-causaldata-titanic’s home link. R package:causaldata R Dataset:titanic

258. Simulated data from a job training program for a bias reduction method

name:rdataset-causaldata-training_bias_reduction reference:rdataset-causaldata-training_bias_reduction’s home link. R package:causaldata R Dataset:training_bias_reduction

259. Simulated data from a job training program

name:rdataset-causaldata-training_example reference:rdataset-causaldata-training_example’s home link. R package:causaldata R Dataset:training_example

260. Data on 19th century English Poverty from Yule (1899)

name:rdataset-causaldata-yule reference:rdataset-causaldata-yule’s home link. R package:causaldata R Dataset:yule

261. European Union Agricultural Workforces

name:rdataset-cluster-agriculture reference:rdataset-cluster-agriculture’s home link. R package:cluster R Dataset:agriculture

262. Attributes of Animals

name:rdataset-cluster-animals reference:rdataset-cluster-animals’s home link. R package:cluster R Dataset:animals

263. Subset of C-horizon of Kola Data

name:rdataset-cluster-chorsub reference:rdataset-cluster-chorsub’s home link. R package:cluster R Dataset:chorsub

264. Flower Characteristics

name:rdataset-cluster-flower reference:rdataset-cluster-flower’s home link. R package:cluster R Dataset:flower

265. Plant Species Traits Data

name:rdataset-cluster-planttraits reference:rdataset-cluster-planttraits’s home link. R package:cluster R Dataset:planttraits

266. Isotopic Composition Plutonium Batches

name:rdataset-cluster-pluton reference:rdataset-cluster-pluton’s home link. R package:cluster R Dataset:pluton

267. Ruspini Data

name:rdataset-cluster-ruspini reference:rdataset-cluster-ruspini’s home link. R package:cluster R Dataset:ruspini

268. Votes for Republican Candidate in Presidential Elections

name:rdataset-cluster-votes.repub reference:rdataset-cluster-votes.repub’s home link. R package:cluster R Dataset:votes.repub

269. Bivariate Data Set with 3 Clusters

name:rdataset-cluster-xclara reference:rdataset-cluster-xclara’s home link. R package:cluster R Dataset:xclara

270. affairs

name:rdataset-count-affairs reference:rdataset-count-affairs’s home link. R package:count R Dataset:affairs

271. azcabgptca

name:rdataset-count-azcabgptca reference:rdataset-count-azcabgptca’s home link. R package:count R Dataset:azcabgptca

272. azdrg112

name:rdataset-count-azdrg112 reference:rdataset-count-azdrg112’s home link. R package:count R Dataset:azdrg112

273. azpro

name:rdataset-count-azpro reference:rdataset-count-azpro’s home link. R package:count R Dataset:azpro

274. azprocedure

name:rdataset-count-azprocedure reference:rdataset-count-azprocedure’s home link. R package:count R Dataset:azprocedure

275. badhealth

name:rdataset-count-badhealth reference:rdataset-count-badhealth’s home link. R package:count R Dataset:badhealth

276. fasttrakg

name:rdataset-count-fasttrakg reference:rdataset-count-fasttrakg’s home link. R package:count R Dataset:fasttrakg

277. fishing

name:rdataset-count-fishing reference:rdataset-count-fishing’s home link. R package:count R Dataset:fishing

278. lbw

name:rdataset-count-lbw reference:rdataset-count-lbw’s home link. R package:count R Dataset:lbw

279. lbwgrp

name:rdataset-count-lbwgrp reference:rdataset-count-lbwgrp’s home link. R package:count R Dataset:lbwgrp

280. loomis

name:rdataset-count-loomis reference:rdataset-count-loomis’s home link. R package:count R Dataset:loomis

281. mdvis

name:rdataset-count-mdvis reference:rdataset-count-mdvis’s home link. R package:count R Dataset:mdvis

282. medpar

name:rdataset-count-medpar reference:rdataset-count-medpar’s home link. R package:count R Dataset:medpar

283. nuts

name:rdataset-count-nuts reference:rdataset-count-nuts’s home link. R package:count R Dataset:nuts

284. rwm

name:rdataset-count-rwm reference:rdataset-count-rwm’s home link. R package:count R Dataset:rwm

285. rwm1984

name:rdataset-count-rwm1984 reference:rdataset-count-rwm1984’s home link. R package:count R Dataset:rwm1984

286. rwm5yr

name:rdataset-count-rwm5yr reference:rdataset-count-rwm5yr’s home link. R package:count R Dataset:rwm5yr

287. ships

name:rdataset-count-ships reference:rdataset-count-ships’s home link. R package:count R Dataset:ships

288. smoking

name:rdataset-count-smoking reference:rdataset-count-smoking’s home link. R package:count R Dataset:smoking

289. titanic

name:rdataset-count-titanic reference:rdataset-count-titanic’s home link. R package:count R Dataset:titanic

290. titanicgrp

name:rdataset-count-titanicgrp reference:rdataset-count-titanicgrp’s home link. R package:count R Dataset:titanicgrp

291. Precipitation Observations and Forecasts for Innsbruck

name:rdataset-crch-rainibk reference:rdataset-crch-rainibk’s home link. R package:crch R Dataset:rainibk

292. Aberrant Crypt Foci in Rat Colons

name:rdataset-daag-acf1 reference:rdataset-daag-acf1’s home link. R package:daag R Dataset:acf1

293. Australian athletes data set

name:rdataset-daag-ais reference:rdataset-daag-ais’s home link. R package:daag R Dataset:ais

294. Measurements on a Selection of Books

name:rdataset-daag-allbacks reference:rdataset-daag-allbacks’s home link. R package:daag R Dataset:allbacks

295. Anesthetic Effectiveness

name:rdataset-daag-anesthetic reference:rdataset-daag-anesthetic’s home link. R package:daag R Dataset:anesthetic

296. Averages by block of corn yields, for treatment 111 only

name:rdataset-daag-ant111b reference:rdataset-daag-ant111b’s home link. R package:daag R Dataset:ant111b

297. Averages by block of yields for the Antigua Corn data

name:rdataset-daag-antigua reference:rdataset-daag-antigua’s home link. R package:daag R Dataset:antigua

298. Tasting experiment that compared four apple varieties

name:rdataset-daag-appletaste reference:rdataset-daag-appletaste’s home link. R package:daag R Dataset:appletaste

299. Latitudes and longitudes for ten Australian cities

name:rdataset-daag-aulatlong reference:rdataset-daag-aulatlong’s home link. R package:daag R Dataset:aulatlong

300. Population figures for Australian States and Territories

name:rdataset-daag-austpop reference:rdataset-daag-austpop’s home link. R package:daag R Dataset:austpop

301. Biomass Data

name:rdataset-daag-biomass reference:rdataset-daag-biomass’s home link. R package:daag R Dataset:biomass

302. Australian and Related Historical Annual Climate Data, by region

name:rdataset-daag-bomregions reference:rdataset-daag-bomregions’s home link. R package:daag R Dataset:bomregions

303. Australian and Related Historical Annual Climate Data, by region

name:rdataset-daag-bomregions2011 reference:rdataset-daag-bomregions2011’s home link. R package:daag R Dataset:bomregions2011

304. Australian and Related Historical Annual Climate Data, by region

name:rdataset-daag-bomregions2012 reference:rdataset-daag-bomregions2012’s home link. R package:daag R Dataset:bomregions2012

305. Southern Oscillation Index Data

name:rdataset-daag-bomsoi reference:rdataset-daag-bomsoi’s home link. R package:daag R Dataset:bomsoi

306. Southern Oscillation Index Data

name:rdataset-daag-bomsoi2001 reference:rdataset-daag-bomsoi2001’s home link. R package:daag R Dataset:bomsoi2001

307. Boston Housing Data - Corrected

name:rdataset-daag-bostonc reference:rdataset-daag-bostonc’s home link. R package:daag R Dataset:bostonc

308. US Car Price Data

name:rdataset-daag-carprice reference:rdataset-daag-carprice’s home link. R package:daag R Dataset:carprice

309. A Summary of the Cars93 Data set

name:rdataset-daag-cars93.summary reference:rdataset-daag-cars93.summary’s home link. R package:daag R Dataset:cars93.summary

310. Percentage of Sugar in Breakfast Cereal

name:rdataset-daag-cerealsugar reference:rdataset-daag-cerealsugar’s home link. R package:daag R Dataset:cerealsugar

311. Cape Fur Seal Data

name:rdataset-daag-cfseal reference:rdataset-daag-cfseal’s home link. R package:daag R Dataset:cfseal

312. Populations of Major Canadian Cities (1992-96)

name:rdataset-daag-cities reference:rdataset-daag-cities’s home link. R package:daag R Dataset:cities

313. Dose-mortality data, for fumigation of codling moth with methyl bromide

name:rdataset-daag-codling reference:rdataset-daag-codling’s home link. R package:daag R Dataset:codling

314. Occupation and wage profiles of British cotton workers

name:rdataset-daag-cottonworkers reference:rdataset-daag-cottonworkers’s home link. R package:daag R Dataset:cottonworkers

315. Labour Training Evaluation Data

name:rdataset-daag-cps1 reference:rdataset-daag-cps1’s home link. R package:daag R Dataset:cps1

316. Labour Training Evaluation Data

name:rdataset-daag-cps2 reference:rdataset-daag-cps2’s home link. R package:daag R Dataset:cps2

317. Labour Training Evaluation Data

name:rdataset-daag-cps3 reference:rdataset-daag-cps3’s home link. R package:daag R Dataset:cps3

318. Lifespans of UK 1st class cricketers born 1840-1960

name:rdataset-daag-cricketer reference:rdataset-daag-cricketer’s home link. R package:daag R Dataset:cricketer

319. Comparison of cuckoo eggs with host eggs

name:rdataset-daag-cuckoohosts reference:rdataset-daag-cuckoohosts’s home link. R package:daag R Dataset:cuckoohosts

320. Cuckoo Eggs Data

name:rdataset-daag-cuckoos reference:rdataset-daag-cuckoos’s home link. R package:daag R Dataset:cuckoos

321. Dengue prevalence, by administrative region

name:rdataset-daag-dengue reference:rdataset-daag-dengue’s home link. R package:daag R Dataset:dengue

322. Dewpoint Data

name:rdataset-daag-dewpoint reference:rdataset-daag-dewpoint’s home link. R package:daag R Dataset:dewpoint

323. Periods Between Rain Events

name:rdataset-daag-droughts reference:rdataset-daag-droughts’s home link. R package:daag R Dataset:droughts

324. EPICA Dome C Ice Core 800KYr Carbon Dioxide Data

name:rdataset-daag-edcco2 reference:rdataset-daag-edcco2’s home link. R package:daag R Dataset:edcco2

325. EPICA Dome C Ice Core 800KYr Temperature Estimates

name:rdataset-daag-edct reference:rdataset-daag-edct’s home link. R package:daag R Dataset:edct

326. Elastic Band Data Replicated

name:rdataset-daag-elastic1 reference:rdataset-daag-elastic1’s home link. R package:daag R Dataset:elastic1

327. Elastic Band Data Replicated Again

name:rdataset-daag-elastic2 reference:rdataset-daag-elastic2’s home link. R package:daag R Dataset:elastic2

328. Elastic Band Data

name:rdataset-daag-elasticband reference:rdataset-daag-elasticband’s home link. R package:daag R Dataset:elasticband

329. Fossil Fuel Data

name:rdataset-daag-fossilfuel reference:rdataset-daag-fossilfuel’s home link. R package:daag R Dataset:fossilfuel

330. Female Possum Measurements

name:rdataset-daag-fossum reference:rdataset-daag-fossum’s home link. R package:daag R Dataset:fossum

331. Frogs Data

name:rdataset-daag-frogs reference:rdataset-daag-frogs’s home link. R package:daag R Dataset:frogs

332. Frosted Flakes data

name:rdataset-daag-frostedflakes reference:rdataset-daag-frostedflakes’s home link. R package:daag R Dataset:frostedflakes

333. Electrical Resistance of Kiwi Fruit

name:rdataset-daag-fruitohms reference:rdataset-daag-fruitohms’s home link. R package:daag R Dataset:fruitohms

334. Effect of pentazocine on post-operative pain (average VAS scores)

name:rdataset-daag-gaba reference:rdataset-daag-gaba’s home link. R package:daag R Dataset:gaba

335. Seismic Timing Data

name:rdataset-daag-geophones reference:rdataset-daag-geophones’s home link. R package:daag R Dataset:geophones

336. Yearly averages of Great Lake heights: 1918 - 2009

name:rdataset-daag-greatlakes reference:rdataset-daag-greatlakes’s home link. R package:daag R Dataset:greatlakes

337. Alcohol consumption in Australia and New Zealand

name:rdataset-daag-grog reference:rdataset-daag-grog’s home link. R package:daag R Dataset:grog

338. Minor Head Injury (Simulated) Data

name:rdataset-daag-head.injury reference:rdataset-daag-head.injury’s home link. R package:daag R Dataset:head.injury

339. Minor Head Injury (Simulated) Data

name:rdataset-daag-headinjury reference:rdataset-daag-headinjury’s home link. R package:daag R Dataset:headinjury

340. Scottish Hill Races Data

name:rdataset-daag-hills reference:rdataset-daag-hills’s home link. R package:daag R Dataset:hills

341. Scottish Hill Races Data - 2000

name:rdataset-daag-hills2000 reference:rdataset-daag-hills2000’s home link. R package:daag R Dataset:hills2000

342. Hawaian island chain hotspot Potassium-Argon ages

name:rdataset-daag-hotspots reference:rdataset-daag-hotspots’s home link. R package:daag R Dataset:hotspots

343. Hawaian island chain hotspot Argon-Argon ages

name:rdataset-daag-hotspots2006 reference:rdataset-daag-hotspots2006’s home link. R package:daag R Dataset:hotspots2006

344. Aranda House Prices

name:rdataset-daag-houseprices reference:rdataset-daag-houseprices’s home link. R package:daag R Dataset:houseprices

345. Oxygen uptake versus mechanical power, for humans

name:rdataset-daag-humanpower1 reference:rdataset-daag-humanpower1’s home link. R package:daag R Dataset:humanpower1

346. Oxygen uptake versus mechanical power, for humans

name:rdataset-daag-humanpower2 reference:rdataset-daag-humanpower2’s home link. R package:daag R Dataset:humanpower2

347. Named US Atlantic Hurricanes

name:rdataset-daag-hurricnamed reference:rdataset-daag-hurricnamed’s home link. R package:daag R Dataset:hurricnamed

348. Blood pressure versus Salt; inter-population data

name:rdataset-daag-intersalt reference:rdataset-daag-intersalt’s home link. R package:daag R Dataset:intersalt

349. Iron Content Measurements

name:rdataset-daag-ironslag reference:rdataset-daag-ironslag’s home link. R package:daag R Dataset:ironslag

350. Canadian Labour Force Summary Data (1995-96)

name:rdataset-daag-jobs reference:rdataset-daag-jobs’s home link. R package:daag R Dataset:jobs

351. Kiwi Shading Data

name:rdataset-daag-kiwishade reference:rdataset-daag-kiwishade’s home link. R package:daag R Dataset:kiwishade

352. Full Leaf Shape Data Set

name:rdataset-daag-leafshape reference:rdataset-daag-leafshape’s home link. R package:daag R Dataset:leafshape

353. Subset of Leaf Shape Data Set

name:rdataset-daag-leafshape17 reference:rdataset-daag-leafshape17’s home link. R package:daag R Dataset:leafshape17

354. Leaf and Air Temperature Data

name:rdataset-daag-leaftemp reference:rdataset-daag-leaftemp’s home link. R package:daag R Dataset:leaftemp

355. Full Leaf and Air Temperature Data Set

name:rdataset-daag-leaftemp.all reference:rdataset-daag-leaftemp.all’s home link. R package:daag R Dataset:leaftemp.all

356. Mouse Litters

name:rdataset-daag-litters reference:rdataset-daag-litters’s home link. R package:daag R Dataset:litters

357. Ontario Lottery Data

name:rdataset-daag-lottario reference:rdataset-daag-lottario’s home link. R package:daag R Dataset:lottario

358. Cape Fur Seal Lung Measurements

name:rdataset-daag-lung reference:rdataset-daag-lung’s home link. R package:daag R Dataset:lung

359. The Nine Largest Lakes in Manitoba

name:rdataset-daag-manitoba.lakes reference:rdataset-daag-manitoba.lakes’s home link. R package:daag R Dataset:manitoba.lakes

360. Deaths in London from measles

name:rdataset-daag-measles reference:rdataset-daag-measles’s home link. R package:daag R Dataset:measles

361. Family Medical Expenses

name:rdataset-daag-medexpenses reference:rdataset-daag-medexpenses’s home link. R package:daag R Dataset:medexpenses

362. Mortality Outcomes for Females Suffering Myocardial Infarction

name:rdataset-daag-mifem reference:rdataset-daag-mifem’s home link. R package:daag R Dataset:mifem

363. Darwin’s Wild Mignonette Data

name:rdataset-daag-mignonette reference:rdataset-daag-mignonette’s home link. R package:daag R Dataset:mignonette

364. Milk Sweetness Study

name:rdataset-daag-milk reference:rdataset-daag-milk’s home link. R package:daag R Dataset:milk

365. Model Car Data

name:rdataset-daag-modelcars reference:rdataset-daag-modelcars’s home link. R package:daag R Dataset:modelcars

366. WHO Monica Data

name:rdataset-daag-monica reference:rdataset-daag-monica’s home link. R package:daag R Dataset:monica

367. Moths Data

name:rdataset-daag-moths reference:rdataset-daag-moths’s home link. R package:daag R Dataset:moths

368. Airbag and other influences on accident fatalities

name:rdataset-daag-nasscds reference:rdataset-daag-nasscds’s home link. R package:daag R Dataset:nasscds

369. Documentation of names of columns in nass9702cor

name:rdataset-daag-nasshead reference:rdataset-daag-nasshead’s home link. R package:daag R Dataset:nasshead

370. Record times for Northern Ireland mountain running events

name:rdataset-daag-nihills reference:rdataset-daag-nihills’s home link. R package:daag R Dataset:nihills

371. Labour Training Evaluation Data

name:rdataset-daag-nsw74demo reference:rdataset-daag-nsw74demo’s home link. R package:daag R Dataset:nsw74demo

372. Labour Training Evaluation Data

name:rdataset-daag-nsw74psid1 reference:rdataset-daag-nsw74psid1’s home link. R package:daag R Dataset:nsw74psid1

373. Labour Training Evaluation Data

name:rdataset-daag-nsw74psid3 reference:rdataset-daag-nsw74psid3’s home link. R package:daag R Dataset:nsw74psid3

374. A Subset of the nsw74psid1 Data Set

name:rdataset-daag-nsw74psida reference:rdataset-daag-nsw74psida’s home link. R package:daag R Dataset:nsw74psida

375. Labour Training Evaluation Data

name:rdataset-daag-nswdemo reference:rdataset-daag-nswdemo’s home link. R package:daag R Dataset:nswdemo

376. Labour Training Evaluation Data

name:rdataset-daag-nswpsid1 reference:rdataset-daag-nswpsid1’s home link. R package:daag R Dataset:nswpsid1

377. Measurements on 12 books

name:rdataset-daag-oddbooks reference:rdataset-daag-oddbooks’s home link. R package:daag R Dataset:oddbooks

378. Challenger O-rings Data

name:rdataset-daag-orings reference:rdataset-daag-orings’s home link. R package:daag R Dataset:orings

379. Ozone Data

name:rdataset-daag-ozone reference:rdataset-daag-ozone’s home link. R package:daag R Dataset:ozone

380. Heated Elastic Bands

name:rdataset-daag-pair65 reference:rdataset-daag-pair65’s home link. R package:daag R Dataset:pair65

381. Possum Measurements

name:rdataset-daag-possum reference:rdataset-daag-possum’s home link. R package:daag R Dataset:possum

382. Possum Sites

name:rdataset-daag-possumsites reference:rdataset-daag-possumsites’s home link. R package:daag R Dataset:possumsites

383. Deaths from various causes, in London from 1629 till 1881, with gaps

name:rdataset-daag-poxetc reference:rdataset-daag-poxetc’s home link. R package:daag R Dataset:poxetc

384. Primate Body and Brain Weights

name:rdataset-daag-primates reference:rdataset-daag-primates’s home link. R package:daag R Dataset:primates

385. Progression of Record times for track races, 1912 - 2008

name:rdataset-daag-progression reference:rdataset-daag-progression’s home link. R package:daag R Dataset:progression

386. Labour Training Evaluation Data

name:rdataset-daag-psid1 reference:rdataset-daag-psid1’s home link. R package:daag R Dataset:psid1

387. Labour Training Evaluation Data

name:rdataset-daag-psid2 reference:rdataset-daag-psid2’s home link. R package:daag R Dataset:psid2

388. Labour Training Evaluation Data

name:rdataset-daag-psid3 reference:rdataset-daag-psid3’s home link. R package:daag R Dataset:psid3

389. Scottish Hill Races Data - 2000

name:rdataset-daag-races2000 reference:rdataset-daag-races2000’s home link. R package:daag R Dataset:races2000

390. Rainforest Data

name:rdataset-daag-rainforest reference:rdataset-daag-rainforest’s home link. R package:daag R Dataset:rainforest

391. Rare and Endangered Plant Species

name:rdataset-daag-rareplants reference:rdataset-daag-rareplants’s home link. R package:daag R Dataset:rareplants

392. Genetically Modified and Wild Type Rice Data

name:rdataset-daag-rice reference:rdataset-daag-rice’s home link. R package:daag R Dataset:rice

393. Pacific Rock Art features

name:rdataset-daag-rockart reference:rdataset-daag-rockart’s home link. R package:daag R Dataset:rockart

394. Lawn Roller Data

name:rdataset-daag-roller reference:rdataset-daag-roller’s home link. R package:daag R Dataset:roller

395. School Science Survey Data

name:rdataset-daag-science reference:rdataset-daag-science’s home link. R package:daag R Dataset:science

396. Barley Seeding Rate Data

name:rdataset-daag-seedrates reference:rdataset-daag-seedrates’s home link. R package:daag R Dataset:seedrates

397. Social Support Data

name:rdataset-daag-socsupport reference:rdataset-daag-socsupport’s home link. R package:daag R Dataset:socsupport

398. Measurements on a Selection of Paperback Books

name:rdataset-daag-softbacks reference:rdataset-daag-softbacks’s home link. R package:daag R Dataset:softbacks

399. sorption data set

name:rdataset-daag-sorption reference:rdataset-daag-sorption’s home link. R package:daag R Dataset:sorption

400. Closing Numbers for S and P 500 Index

name:rdataset-daag-sp500close reference:rdataset-daag-sp500close’s home link. R package:daag R Dataset:sp500close

401. Closing Numbers for S and P 500 Index - First 100 Days of 1990

name:rdataset-daag-sp500w90 reference:rdataset-daag-sp500w90’s home link. R package:daag R Dataset:sp500w90

402. Spam E-mail Data

name:rdataset-daag-spam7 reference:rdataset-daag-spam7’s home link. R package:daag R Dataset:spam7

403. Averages by block of yields for the St. Vincent Corn data

name:rdataset-daag-stvincent reference:rdataset-daag-stvincent’s home link. R package:daag R Dataset:stvincent

404. Sugar Data

name:rdataset-daag-sugar reference:rdataset-daag-sugar’s home link. R package:daag R Dataset:sugar

405. Car Window Tinting Experiment Data

name:rdataset-daag-tinting reference:rdataset-daag-tinting’s home link. R package:daag R Dataset:tinting

406. Root weights of tomato plants exposed to 4 different treatments

name:rdataset-daag-tomato reference:rdataset-daag-tomato’s home link. R package:daag R Dataset:tomato

407. Toy Cars Data

name:rdataset-daag-toycars reference:rdataset-daag-toycars’s home link. R package:daag R Dataset:toycars

408. Averages by block of corn yields, for treatment 111 only

name:rdataset-daag-vince111b reference:rdataset-daag-vince111b’s home link. R package:daag R Dataset:vince111b

409. Video Lottery Terminal Data

name:rdataset-daag-vlt reference:rdataset-daag-vlt’s home link. R package:daag R Dataset:vlt

410. Wages of Lancashire Cotton Factory Workers in 1833

name:rdataset-daag-wages1833 reference:rdataset-daag-wages1833’s home link. R package:daag R Dataset:wages1833

411. Deaths from whooping cough, in London

name:rdataset-daag-whoops reference:rdataset-daag-whoops’s home link. R package:daag R Dataset:whoops

412. Record times for track and road races, at August 9th 2006

name:rdataset-daag-worldrecords reference:rdataset-daag-worldrecords’s home link. R package:daag R Dataset:worldrecords

413. Ability and Intelligence Tests

name:rdataset-datasets-ability.cov reference:rdataset-datasets-ability.cov’s home link. R package:datasets R Dataset:ability.cov

414. Passenger Miles on Commercial US Airlines, 1937-1960

name:rdataset-datasets-airmiles reference:rdataset-datasets-airmiles’s home link. R package:datasets R Dataset:airmiles

415. Monthly Airline Passenger Numbers 1949-1960

name:rdataset-datasets-airpassengers reference:rdataset-datasets-airpassengers’s home link. R package:datasets R Dataset:airpassengers

416. New York Air Quality Measurements

name:rdataset-datasets-airquality reference:rdataset-datasets-airquality’s home link. R package:datasets R Dataset:airquality

417. Anscombe’s Quartet of ‘Identical’ Simple Linear Regressions

name:rdataset-datasets-anscombe reference:rdataset-datasets-anscombe’s home link. R package:datasets R Dataset:anscombe

418. The Joyner-Boore Attenuation Data

name:rdataset-datasets-attenu reference:rdataset-datasets-attenu’s home link. R package:datasets R Dataset:attenu

419. The Chatterjee-Price Attitude Data

name:rdataset-datasets-attitude reference:rdataset-datasets-attitude’s home link. R package:datasets R Dataset:attitude

420. Quarterly Time Series of the Number of Australian Residents

name:rdataset-datasets-austres reference:rdataset-datasets-austres’s home link. R package:datasets R Dataset:austres

421. Sales Data with Leading Indicator

name:rdataset-datasets-bjsales reference:rdataset-datasets-bjsales’s home link. R package:datasets R Dataset:bjsales

422. Biochemical Oxygen Demand

name:rdataset-datasets-bod reference:rdataset-datasets-bod’s home link. R package:datasets R Dataset:bod

423. Speed and Stopping Distances of Cars

name:rdataset-datasets-cars reference:rdataset-datasets-cars’s home link. R package:datasets R Dataset:cars

424. Weight versus age of chicks on different diets

name:rdataset-datasets-chickweight reference:rdataset-datasets-chickweight’s home link. R package:datasets R Dataset:chickweight

425. Chicken Weights by Feed Type

name:rdataset-datasets-chickwts reference:rdataset-datasets-chickwts’s home link. R package:datasets R Dataset:chickwts

426. Mauna Loa Atmospheric CO2 Concentration

name:rdataset-datasets-co2 reference:rdataset-datasets-co2’s home link. R package:datasets R Dataset:co2

427. Student’s 3000 Criminals Data

name:rdataset-datasets-crimtab reference:rdataset-datasets-crimtab’s home link. R package:datasets R Dataset:crimtab

428. Yearly Numbers of Important Discoveries

name:rdataset-datasets-discoveries reference:rdataset-datasets-discoveries’s home link. R package:datasets R Dataset:discoveries

429. Elisa assay of DNase

name:rdataset-datasets-dnase reference:rdataset-datasets-dnase’s home link. R package:datasets R Dataset:dnase

430. Smoking, Alcohol and (O)esophageal Cancer

name:rdataset-datasets-esoph reference:rdataset-datasets-esoph’s home link. R package:datasets R Dataset:esoph

431. Conversion Rates of Euro Currencies

name:rdataset-datasets-euro reference:rdataset-datasets-euro’s home link. R package:datasets R Dataset:euro

432. Daily Closing Prices of Major European Stock Indices, 1991-1998

name:rdataset-datasets-eustockmarkets reference:rdataset-datasets-eustockmarkets’s home link. R package:datasets R Dataset:eustockmarkets

433. Old Faithful Geyser Data

name:rdataset-datasets-faithful reference:rdataset-datasets-faithful’s home link. R package:datasets R Dataset:faithful

434. Determination of Formaldehyde

name:rdataset-datasets-formaldehyde reference:rdataset-datasets-formaldehyde’s home link. R package:datasets R Dataset:formaldehyde

435. Freeny’s Revenue Data

name:rdataset-datasets-freeny reference:rdataset-datasets-freeny’s home link. R package:datasets R Dataset:freeny

436. Hair and Eye Color of Statistics Students

name:rdataset-datasets-haireyecolor reference:rdataset-datasets-haireyecolor’s home link. R package:datasets R Dataset:haireyecolor

437. Harman Example 2.3

name:rdataset-datasets-harman23.cor reference:rdataset-datasets-harman23.cor’s home link. R package:datasets R Dataset:harman23.cor

438. Harman Example 7.4

name:rdataset-datasets-harman74.cor reference:rdataset-datasets-harman74.cor’s home link. R package:datasets R Dataset:harman74.cor

439. Pharmacokinetics of Indomethacin

name:rdataset-datasets-indometh reference:rdataset-datasets-indometh’s home link. R package:datasets R Dataset:indometh

440. Infertility after Spontaneous and Induced Abortion

name:rdataset-datasets-infert reference:rdataset-datasets-infert’s home link. R package:datasets R Dataset:infert

441. Effectiveness of Insect Sprays

name:rdataset-datasets-insectsprays reference:rdataset-datasets-insectsprays’s home link. R package:datasets R Dataset:insectsprays

442. Edgar Anderson’s Iris Data

name:rdataset-datasets-iris reference:rdataset-datasets-iris’s home link. R package:datasets R Dataset:iris

443. Edgar Anderson’s Iris Data

name:rdataset-datasets-iris3 reference:rdataset-datasets-iris3’s home link. R package:datasets R Dataset:iris3

444. Areas of the World’s Major Landmasses

name:rdataset-datasets-islands reference:rdataset-datasets-islands’s home link. R package:datasets R Dataset:islands

445. Quarterly Earnings per Johnson & Johnson Share

name:rdataset-datasets-johnsonjohnson reference:rdataset-datasets-johnsonjohnson’s home link. R package:datasets R Dataset:johnsonjohnson

446. Level of Lake Huron 1875-1972

name:rdataset-datasets-lakehuron reference:rdataset-datasets-lakehuron’s home link. R package:datasets R Dataset:lakehuron

447. Luteinizing Hormone in Blood Samples

name:rdataset-datasets-lh reference:rdataset-datasets-lh’s home link. R package:datasets R Dataset:lh

448. Intercountry Life-Cycle Savings Data

name:rdataset-datasets-lifecyclesavings reference:rdataset-datasets-lifecyclesavings’s home link. R package:datasets R Dataset:lifecyclesavings

449. Growth of Loblolly pine trees

name:rdataset-datasets-loblolly reference:rdataset-datasets-loblolly’s home link. R package:datasets R Dataset:loblolly

450. Longley’s Economic Regression Data

name:rdataset-datasets-longley reference:rdataset-datasets-longley’s home link. R package:datasets R Dataset:longley

451. Annual Canadian Lynx trappings 1821-1934

name:rdataset-datasets-lynx reference:rdataset-datasets-lynx’s home link. R package:datasets R Dataset:lynx

452. Michelson Speed of Light Data

name:rdataset-datasets-morley reference:rdataset-datasets-morley’s home link. R package:datasets R Dataset:morley

453. Motor Trend Car Road Tests

name:rdataset-datasets-mtcars reference:rdataset-datasets-mtcars’s home link. R package:datasets R Dataset:mtcars

454. Average Yearly Temperatures in New Haven

name:rdataset-datasets-nhtemp reference:rdataset-datasets-nhtemp’s home link. R package:datasets R Dataset:nhtemp

455. Flow of the River Nile

name:rdataset-datasets-nile reference:rdataset-datasets-nile’s home link. R package:datasets R Dataset:nile

456. Average Monthly Temperatures at Nottingham, 1920-1939

name:rdataset-datasets-nottem reference:rdataset-datasets-nottem’s home link. R package:datasets R Dataset:nottem

457. Classical N, P, K Factorial Experiment

name:rdataset-datasets-npk reference:rdataset-datasets-npk’s home link. R package:datasets R Dataset:npk

458. Occupational Status of Fathers and their Sons

name:rdataset-datasets-occupationalstatus reference:rdataset-datasets-occupationalstatus’s home link. R package:datasets R Dataset:occupationalstatus

459. Growth of Orange Trees

name:rdataset-datasets-orange reference:rdataset-datasets-orange’s home link. R package:datasets R Dataset:orange

460. Potency of Orchard Sprays

name:rdataset-datasets-orchardsprays reference:rdataset-datasets-orchardsprays’s home link. R package:datasets R Dataset:orchardsprays

461. Results from an Experiment on Plant Growth

name:rdataset-datasets-plantgrowth reference:rdataset-datasets-plantgrowth’s home link. R package:datasets R Dataset:plantgrowth

462. Annual Precipitation in US Cities

name:rdataset-datasets-precip reference:rdataset-datasets-precip’s home link. R package:datasets R Dataset:precip

463. Quarterly Approval Ratings of US Presidents

name:rdataset-datasets-presidents reference:rdataset-datasets-presidents’s home link. R package:datasets R Dataset:presidents

464. Vapor Pressure of Mercury as a Function of Temperature

name:rdataset-datasets-pressure reference:rdataset-datasets-pressure’s home link. R package:datasets R Dataset:pressure

465. Reaction Velocity of an Enzymatic Reaction

name:rdataset-datasets-puromycin reference:rdataset-datasets-puromycin’s home link. R package:datasets R Dataset:puromycin

466. Locations of Earthquakes off Fiji

name:rdataset-datasets-quakes reference:rdataset-datasets-quakes’s home link. R package:datasets R Dataset:quakes

467. Random Numbers from Congruential Generator RANDU

name:rdataset-datasets-randu reference:rdataset-datasets-randu’s home link. R package:datasets R Dataset:randu

468. Lengths of Major North American Rivers

name:rdataset-datasets-rivers reference:rdataset-datasets-rivers’s home link. R package:datasets R Dataset:rivers

469. Measurements on Petroleum Rock Samples

name:rdataset-datasets-rock reference:rdataset-datasets-rock’s home link. R package:datasets R Dataset:rock

470. Road Casualties in Great Britain 1969-84

name:rdataset-datasets-seatbelts reference:rdataset-datasets-seatbelts’s home link. R package:datasets R Dataset:seatbelts

471. Student’s Sleep Data

name:rdataset-datasets-sleep reference:rdataset-datasets-sleep’s home link. R package:datasets R Dataset:sleep

472. Brownlee’s Stack Loss Plant Data

name:rdataset-datasets-stackloss reference:rdataset-datasets-stackloss’s home link. R package:datasets R Dataset:stackloss

473. Monthly Sunspot Data, from 1749 to “Present”

name:rdataset-datasets-sunspot.month reference:rdataset-datasets-sunspot.month’s home link. R package:datasets R Dataset:sunspot.month

474. Yearly Sunspot Data, 1700-1988

name:rdataset-datasets-sunspot.year reference:rdataset-datasets-sunspot.year’s home link. R package:datasets R Dataset:sunspot.year

475. Monthly Sunspot Numbers, 1749-1983

name:rdataset-datasets-sunspots reference:rdataset-datasets-sunspots’s home link. R package:datasets R Dataset:sunspots

476. Swiss Fertility and Socioeconomic Indicators (1888) Data

name:rdataset-datasets-swiss reference:rdataset-datasets-swiss’s home link. R package:datasets R Dataset:swiss

477. Pharmacokinetics of Theophylline

name:rdataset-datasets-theoph reference:rdataset-datasets-theoph’s home link. R package:datasets R Dataset:theoph

478. Survival of passengers on the Titanic

name:rdataset-datasets-titanic reference:rdataset-datasets-titanic’s home link. R package:datasets R Dataset:titanic

479. The Effect of Vitamin C on Tooth Growth in Guinea Pigs

name:rdataset-datasets-toothgrowth reference:rdataset-datasets-toothgrowth’s home link. R package:datasets R Dataset:toothgrowth

480. Yearly Treering Data, -6000-1979

name:rdataset-datasets-treering reference:rdataset-datasets-treering’s home link. R package:datasets R Dataset:treering

481. Diameter, Height and Volume for Black Cherry Trees

name:rdataset-datasets-trees reference:rdataset-datasets-trees’s home link. R package:datasets R Dataset:trees

482. Student Admissions at UC Berkeley

name:rdataset-datasets-ucbadmissions reference:rdataset-datasets-ucbadmissions’s home link. R package:datasets R Dataset:ucbadmissions

483. Road Casualties in Great Britain 1969-84

name:rdataset-datasets-ukdriverdeaths reference:rdataset-datasets-ukdriverdeaths’s home link. R package:datasets R Dataset:ukdriverdeaths

484. UK Quarterly Gas Consumption

name:rdataset-datasets-ukgas reference:rdataset-datasets-ukgas’s home link. R package:datasets R Dataset:ukgas

485. Accidental Deaths in the US 1973-1978

name:rdataset-datasets-usaccdeaths reference:rdataset-datasets-usaccdeaths’s home link. R package:datasets R Dataset:usaccdeaths

486. Violent Crime Rates by US State

name:rdataset-datasets-usarrests reference:rdataset-datasets-usarrests’s home link. R package:datasets R Dataset:usarrests

487. Lawyers’ Ratings of State Judges in the US Superior Court

name:rdataset-datasets-usjudgeratings reference:rdataset-datasets-usjudgeratings’s home link. R package:datasets R Dataset:usjudgeratings

488. Personal Expenditure Data

name:rdataset-datasets-uspersonalexpenditure reference:rdataset-datasets-uspersonalexpenditure’s home link. R package:datasets R Dataset:uspersonalexpenditure

489. Populations Recorded by the US Census

name:rdataset-datasets-uspop reference:rdataset-datasets-uspop’s home link. R package:datasets R Dataset:uspop

490. Death Rates in Virginia (1940)

name:rdataset-datasets-vadeaths reference:rdataset-datasets-vadeaths’s home link. R package:datasets R Dataset:vadeaths

491. Topographic Information on Auckland’s Maunga Whau Volcano

name:rdataset-datasets-volcano reference:rdataset-datasets-volcano’s home link. R package:datasets R Dataset:volcano

492. The Number of Breaks in Yarn during Weaving

name:rdataset-datasets-warpbreaks reference:rdataset-datasets-warpbreaks’s home link. R package:datasets R Dataset:warpbreaks

493. Average Heights and Weights for American Women

name:rdataset-datasets-women reference:rdataset-datasets-women’s home link. R package:datasets R Dataset:women

494. The World’s Telephones

name:rdataset-datasets-worldphones reference:rdataset-datasets-worldphones’s home link. R package:datasets R Dataset:worldphones

495. Internet Usage per Minute

name:rdataset-datasets-wwwusage reference:rdataset-datasets-wwwusage’s home link. R package:datasets R Dataset:wwwusage

496. Band membership

name:rdataset-dplyr-band_instruments reference:rdataset-dplyr-band_instruments’s home link. R package:dplyr R Dataset:band_instruments

497. Band membership

name:rdataset-dplyr-band_instruments2 reference:rdataset-dplyr-band_instruments2’s home link. R package:dplyr R Dataset:band_instruments2

498. Band membership

name:rdataset-dplyr-band_members reference:rdataset-dplyr-band_members’s home link. R package:dplyr R Dataset:band_members

499. Starwars characters

name:rdataset-dplyr-starwars reference:rdataset-dplyr-starwars’s home link. R package:dplyr R Dataset:starwars

500. Storm tracks data

name:rdataset-dplyr-storms reference:rdataset-dplyr-storms’s home link. R package:dplyr R Dataset:storms

501. RuPaul’s Drag Race Episode-Contestant Data

name:rdataset-dragracer-rpdr_contep reference:rdataset-dragracer-rpdr_contep’s home link. R package:dragracer R Dataset:rpdr_contep

502. RuPaul’s Drag Race Contestant Data

name:rdataset-dragracer-rpdr_contestants reference:rdataset-dragracer-rpdr_contestants’s home link. R package:dragracer R Dataset:rpdr_contestants

503. RuPaul’s Drag Race Episode Data

name:rdataset-dragracer-rpdr_ep reference:rdataset-dragracer-rpdr_ep’s home link. R package:dragracer R Dataset:rpdr_ep

504. Acifluorfen and diquat tested on Lemna minor.

name:rdataset-drc-acidiq reference:rdataset-drc-acidiq’s home link. R package:drc R Dataset:acidiq

505. Volume of algae as function of increasing concentrations of a herbicide

name:rdataset-drc-algae reference:rdataset-drc-algae’s home link. R package:drc R Dataset:algae

506. Effect of technical grade and commercially formulated auxin herbicides

name:rdataset-drc-auxins reference:rdataset-drc-auxins’s home link. R package:drc R Dataset:auxins

507. Germination of common chickweed (_Stellaria media_)

name:rdataset-drc-chickweed reference:rdataset-drc-chickweed’s home link. R package:drc R Dataset:chickweed

508. Germination of common chickweed (_Stellaria media_)

name:rdataset-drc-chickweed0 reference:rdataset-drc-chickweed0’s home link. R package:drc R Dataset:chickweed0

509. Daphnia test

name:rdataset-drc-daphnids reference:rdataset-drc-daphnids’s home link. R package:drc R Dataset:daphnids

510. Performance of decontaminants used in the culturing of a micro-organism

name:rdataset-drc-decontaminants reference:rdataset-drc-decontaminants’s home link. R package:drc R Dataset:decontaminants

511. Deguelin applied to chrysanthemum aphis

name:rdataset-drc-deguelin reference:rdataset-drc-deguelin’s home link. R package:drc R Dataset:deguelin

512. Earthworm toxicity test

name:rdataset-drc-earthworms reference:rdataset-drc-earthworms’s home link. R package:drc R Dataset:earthworms

513. Effect of erythromycin on mixed sewage microorganisms

name:rdataset-drc-etmotc reference:rdataset-drc-etmotc’s home link. R package:drc R Dataset:etmotc

514. Example from Finney (1971)

name:rdataset-drc-finney71 reference:rdataset-drc-finney71’s home link. R package:drc R Dataset:finney71

515. Herbicide applied to Galium aparine

name:rdataset-drc-g.aparine reference:rdataset-drc-g.aparine’s home link. R package:drc R Dataset:g.aparine

516. Germination of three crops

name:rdataset-drc-germination reference:rdataset-drc-germination’s home link. R package:drc R Dataset:germination

517. Glyphosate and metsulfuron-methyl tested on algae.

name:rdataset-drc-glymet reference:rdataset-drc-glymet’s home link. R package:drc R Dataset:glymet

518. Mortality of tobacco budworms

name:rdataset-drc-h.virescens reference:rdataset-drc-h.virescens’s home link. R package:drc R Dataset:h.virescens

519. Heart rate baroreflexes for rabbits

name:rdataset-drc-heartrate reference:rdataset-drc-heartrate’s home link. R package:drc R Dataset:heartrate

520. Leaf length of barley

name:rdataset-drc-leaflength reference:rdataset-drc-leaflength’s home link. R package:drc R Dataset:leaflength

521. Dose-response profile of degradation of agrochemical using lepidium

name:rdataset-drc-lepidium reference:rdataset-drc-lepidium’s home link. R package:drc R Dataset:lepidium

522. Hormesis in lettuce plants

name:rdataset-drc-lettuce reference:rdataset-drc-lettuce’s home link. R package:drc R Dataset:lettuce

523. Effect of an effluent on the growth of mysid shrimp

name:rdataset-drc-m.bahia reference:rdataset-drc-m.bahia’s home link. R package:drc R Dataset:m.bahia

524. Mechlorprop and terbythylazine tested on Lemna minor

name:rdataset-drc-mecter reference:rdataset-drc-mecter’s home link. R package:drc R Dataset:mecter

525. Data from heavy metal mixture experiments

name:rdataset-drc-metals reference:rdataset-drc-metals’s home link. R package:drc R Dataset:metals

526. Weight gain for different methionine sources

name:rdataset-drc-methionine reference:rdataset-drc-methionine’s home link. R package:drc R Dataset:methionine

527. Dose-response profile of degradation of agrochemical using nasturtium

name:rdataset-drc-nasturtium reference:rdataset-drc-nasturtium’s home link. R package:drc R Dataset:nasturtium

528. Test data from a 21 day fish test

name:rdataset-drc-o.mykiss reference:rdataset-drc-o.mykiss’s home link. R package:drc R Dataset:o.mykiss

529. Effect of sodium pentachlorophenate on growth of fathead minnow

name:rdataset-drc-p.promelas reference:rdataset-drc-p.promelas’s home link. R package:drc R Dataset:p.promelas

530. Competition between two biotypes

name:rdataset-drc-rscompetition reference:rdataset-drc-rscompetition’s home link. R package:drc R Dataset:rscompetition

531. Effect of ferulic acid on growth of ryegrass

name:rdataset-drc-ryegrass reference:rdataset-drc-ryegrass’s home link. R package:drc R Dataset:ryegrass

532. Potency of two herbicides

name:rdataset-drc-s.alba reference:rdataset-drc-s.alba’s home link. R package:drc R Dataset:s.alba

533. Effect of cadmium on growth of green alga

name:rdataset-drc-s.capricornutum reference:rdataset-drc-s.capricornutum’s home link. R package:drc R Dataset:s.capricornutum

534. Root length measurements

name:rdataset-drc-secalonic reference:rdataset-drc-secalonic’s home link. R package:drc R Dataset:secalonic

535. Data from toxicology experiments with selenium

name:rdataset-drc-selenium reference:rdataset-drc-selenium’s home link. R package:drc R Dataset:selenium

536. Inhibition of photosynthesis

name:rdataset-drc-spinach reference:rdataset-drc-spinach’s home link. R package:drc R Dataset:spinach

537. The effect of terbuthylazin on growth rate

name:rdataset-drc-terbuthylazin reference:rdataset-drc-terbuthylazin’s home link. R package:drc R Dataset:terbuthylazin

538. Vinclozolin from AR in vitro assay

name:rdataset-drc-vinclozolin reference:rdataset-drc-vinclozolin’s home link. R package:drc R Dataset:vinclozolin

539. Ship Accidents

name:rdataset-ecdat-accident reference:rdataset-ecdat-accident’s home link. R package:ecdat R Dataset:accident

540. Accountants and Auditors in the US 1850-2016

name:rdataset-ecdat-accountantsauditorspct reference:rdataset-ecdat-accountantsauditorspct’s home link. R package:ecdat R Dataset:accountantsauditorspct

541. Cost for U.S. Airlines

name:rdataset-ecdat-airline reference:rdataset-ecdat-airline’s home link. R package:ecdat R Dataset:airline

542. Air Quality for Californian Metropolitan Areas

name:rdataset-ecdat-airq reference:rdataset-ecdat-airq’s home link. R package:ecdat R Dataset:airq

543. Countries in Banking Crises

name:rdataset-ecdat-bankingcrises reference:rdataset-ecdat-bankingcrises’s home link. R package:ecdat R Dataset:bankingcrises

544. Unemployment of Blue Collar Workers

name:rdataset-ecdat-benefits reference:rdataset-ecdat-benefits’s home link. R package:ecdat R Dataset:benefits

545. Bids Received By U.S. Firms

name:rdataset-ecdat-bids reference:rdataset-ecdat-bids’s home link. R package:ecdat R Dataset:bids

546. Cyber Security Breaches

name:rdataset-ecdat-breaches reference:rdataset-ecdat-breaches’s home link. R package:ecdat R Dataset:breaches

547. Budget Share of Food for Spanish Households

name:rdataset-ecdat-budgetfood reference:rdataset-ecdat-budgetfood’s home link. R package:ecdat R Dataset:budgetfood

548. Budget Shares for Italian Households

name:rdataset-ecdat-budgetitaly reference:rdataset-ecdat-budgetitaly’s home link. R package:ecdat R Dataset:budgetitaly

549. Budget Shares of British Households

name:rdataset-ecdat-budgetuk reference:rdataset-ecdat-budgetuk’s home link. R package:ecdat R Dataset:budgetuk

550. Wages in Belgium

name:rdataset-ecdat-bwages reference:rdataset-ecdat-bwages’s home link. R package:ecdat R Dataset:bwages

551. Stock Market Data

name:rdataset-ecdat-capm reference:rdataset-ecdat-capm’s home link. R package:ecdat R Dataset:capm

552. Stated Preferences for Car Choice

name:rdataset-ecdat-car reference:rdataset-ecdat-car’s home link. R package:ecdat R Dataset:car

553. The California Test Score Data Set

name:rdataset-ecdat-caschool reference:rdataset-ecdat-caschool’s home link. R package:ecdat R Dataset:caschool

554. Choice of Brand for Catsup

name:rdataset-ecdat-catsup reference:rdataset-ecdat-catsup’s home link. R package:ecdat R Dataset:catsup

555. Cigarette Consumption

name:rdataset-ecdat-cigar reference:rdataset-ecdat-cigar’s home link. R package:ecdat R Dataset:cigar

556. The Cigarette Consumption Panel Data Set

name:rdataset-ecdat-cigarette reference:rdataset-ecdat-cigarette’s home link. R package:ecdat R Dataset:cigarette

557. Sales Data of Men’s Fashion Stores

name:rdataset-ecdat-clothing reference:rdataset-ecdat-clothing’s home link. R package:ecdat R Dataset:clothing

558. Prices of Personal Computers

name:rdataset-ecdat-computers reference:rdataset-ecdat-computers’s home link. R package:ecdat R Dataset:computers

559. Quarterly Data on Consumption and Expenditure

name:rdataset-ecdat-consumption reference:rdataset-ecdat-consumption’s home link. R package:ecdat R Dataset:consumption

560. Global cooling from a nuclear war

name:rdataset-ecdat-coolingfromnuclearwar reference:rdataset-ecdat-coolingfromnuclearwar’s home link. R package:ecdat R Dataset:coolingfromnuclearwar

561. Earnings from the Current Population Survey

name:rdataset-ecdat-cpsch3 reference:rdataset-ecdat-cpsch3’s home link. R package:ecdat R Dataset:cpsch3

562. Choice of Brand for Crackers

name:rdataset-ecdat-cracker reference:rdataset-ecdat-cracker’s home link. R package:ecdat R Dataset:cracker

563. Growth of CRAN

name:rdataset-ecdat-cranpackages reference:rdataset-ecdat-cranpackages’s home link. R package:ecdat R Dataset:cranpackages

564. Crime in North Carolina

name:rdataset-ecdat-crime reference:rdataset-ecdat-crime’s home link. R package:ecdat R Dataset:crime

565. Daily Returns from the CRSP Database

name:rdataset-ecdat-crspday reference:rdataset-ecdat-crspday’s home link. R package:ecdat R Dataset:crspday

566. Monthly Returns from the CRSP Database

name:rdataset-ecdat-crspmon reference:rdataset-ecdat-crspmon’s home link. R package:ecdat R Dataset:crspmon

567. Pricing the C’s of Diamond Stones

name:rdataset-ecdat-diamond reference:rdataset-ecdat-diamond’s home link. R package:ecdat R Dataset:diamond

568. DM Dollar Exchange Rate

name:rdataset-ecdat-dm reference:rdataset-ecdat-dm’s home link. R package:ecdat R Dataset:dm

569. Number of Doctor Visits

name:rdataset-ecdat-doctor reference:rdataset-ecdat-doctor’s home link. R package:ecdat R Dataset:doctor

570. Doctor Visits in Australia

name:rdataset-ecdat-doctoraus reference:rdataset-ecdat-doctoraus’s home link. R package:ecdat R Dataset:doctoraus

571. Contacts With Medical Doctor

name:rdataset-ecdat-doctorcontacts reference:rdataset-ecdat-doctorcontacts’s home link. R package:ecdat R Dataset:doctorcontacts

572. Earnings for Three Age Groups

name:rdataset-ecdat-earnings reference:rdataset-ecdat-earnings’s home link. R package:ecdat R Dataset:earnings

573. Cost Function for Electricity Producers

name:rdataset-ecdat-electricity reference:rdataset-ecdat-electricity’s home link. R package:ecdat R Dataset:electricity

574. Extramarital Affairs Data

name:rdataset-ecdat-fair reference:rdataset-ecdat-fair’s home link. R package:ecdat R Dataset:fair

575. Drunk Driving Laws and Traffic Deaths

name:rdataset-ecdat-fatality reference:rdataset-ecdat-fatality’s home link. R package:ecdat R Dataset:fatality

576. Choice of Fishing Mode

name:rdataset-ecdat-fishing reference:rdataset-ecdat-fishing’s home link. R package:ecdat R Dataset:fishing

577. Exchange Rates of US Dollar Against Other Currencies

name:rdataset-ecdat-forward reference:rdataset-ecdat-forward’s home link. R package:ecdat R Dataset:forward

578. Data from the Television Game Show Friend Or Foe ?

name:rdataset-ecdat-friendfoe reference:rdataset-ecdat-friendfoe’s home link. R package:ecdat R Dataset:friendfoe

579. Daily Observations on Exchange Rates of the US Dollar Against Other Currencies

name:rdataset-ecdat-garch reference:rdataset-ecdat-garch’s home link. R package:ecdat R Dataset:garch

580. Gasoline Consumption

name:rdataset-ecdat-gasoline reference:rdataset-ecdat-gasoline’s home link. R package:ecdat R Dataset:gasoline

581. Wage Data

name:rdataset-ecdat-griliches reference:rdataset-ecdat-griliches’s home link. R package:ecdat R Dataset:griliches

582. Grunfeld Investment Data

name:rdataset-ecdat-grunfeld reference:rdataset-ecdat-grunfeld’s home link. R package:ecdat R Dataset:grunfeld

583. Heating and Cooling System Choice in Newly Built Houses in California

name:rdataset-ecdat-hc reference:rdataset-ecdat-hc’s home link. R package:ecdat R Dataset:hc

584. The Boston HMDA Data Set

name:rdataset-ecdat-hdma reference:rdataset-ecdat-hdma’s home link. R package:ecdat R Dataset:hdma

585. Heating System Choice in California Houses

name:rdataset-ecdat-heating reference:rdataset-ecdat-heating’s home link. R package:ecdat R Dataset:heating

586. Hedonic Prices of Census Tracts in Boston

name:rdataset-ecdat-hedonic reference:rdataset-ecdat-hedonic’s home link. R package:ecdat R Dataset:hedonic

587. Cybersecurity breaches reported to the US Department of Health and Human Services

name:rdataset-ecdat-hhscybersecuritybreaches reference:rdataset-ecdat-hhscybersecuritybreaches’s home link. R package:ecdat R Dataset:hhscybersecuritybreaches

588. Health Insurance and Hours Worked By Wives

name:rdataset-ecdat-hi reference:rdataset-ecdat-hi’s home link. R package:ecdat R Dataset:hi

589. The Boston HMDA Data Set

name:rdataset-ecdat-hmda reference:rdataset-ecdat-hmda’s home link. R package:ecdat R Dataset:hmda

590. Sales Prices of Houses in the City of Windsor

name:rdataset-ecdat-housing reference:rdataset-ecdat-housing’s home link. R package:ecdat R Dataset:housing

591. Housing Starts

name:rdataset-ecdat-hstarts reference:rdataset-ecdat-hstarts’s home link. R package:ecdat R Dataset:hstarts

592. Ice Cream Consumption

name:rdataset-ecdat-icecream reference:rdataset-ecdat-icecream’s home link. R package:ecdat R Dataset:icecream

593. Global Terrorism Database yearly summaries

name:rdataset-ecdat-incidents.bycountryyr reference:rdataset-ecdat-incidents.bycountryyr’s home link. R package:ecdat R Dataset:incidents.bycountryyr

594. Income Inequality in the US

name:rdataset-ecdat-incomeinequality reference:rdataset-ecdat-incomeinequality’s home link. R package:ecdat R Dataset:incomeinequality

595. Seasonally Unadjusted Quarterly Data on Disposable Income and Expenditure

name:rdataset-ecdat-incomeuk reference:rdataset-ecdat-incomeuk’s home link. R package:ecdat R Dataset:incomeuk

596. Monthly Interest Rates

name:rdataset-ecdat-irates reference:rdataset-ecdat-irates’s home link. R package:ecdat R Dataset:irates

597. Economic Journals Data Set

name:rdataset-ecdat-journals reference:rdataset-ecdat-journals’s home link. R package:ecdat R Dataset:journals

598. Willingness to Pay for the Preservation of the Kakadu National Park

name:rdataset-ecdat-kakadu reference:rdataset-ecdat-kakadu’s home link. R package:ecdat R Dataset:kakadu

599. Choice of Brand for Ketchup

name:rdataset-ecdat-ketchup reference:rdataset-ecdat-ketchup’s home link. R package:ecdat R Dataset:ketchup

600. Klein’s Model I

name:rdataset-ecdat-klein reference:rdataset-ecdat-klein’s home link. R package:ecdat R Dataset:klein

601. Wages and Hours Worked

name:rdataset-ecdat-laborsupply reference:rdataset-ecdat-laborsupply’s home link. R package:ecdat R Dataset:laborsupply

602. Belgian Firms

name:rdataset-ecdat-labour reference:rdataset-ecdat-labour’s home link. R package:ecdat R Dataset:labour

603. The Longley Data

name:rdataset-ecdat-longley reference:rdataset-ecdat-longley’s home link. R package:ecdat R Dataset:longley

604. Dollar Sterling Exchange Rate

name:rdataset-ecdat-lt reference:rdataset-ecdat-lt’s home link. R package:ecdat R Dataset:lt

605. Macroeconomic Time Series for the United States

name:rdataset-ecdat-macrodat reference:rdataset-ecdat-macrodat’s home link. R package:ecdat R Dataset:macrodat

606. Wages and Education of Young Males

name:rdataset-ecdat-males reference:rdataset-ecdat-males’s home link. R package:ecdat R Dataset:males

607. Manufacturing Costs

name:rdataset-ecdat-manufcost reference:rdataset-ecdat-manufcost’s home link. R package:ecdat R Dataset:manufcost

608. Level of Calculus Attained for Students Taking Advanced Micro-economics

name:rdataset-ecdat-mathlevel reference:rdataset-ecdat-mathlevel’s home link. R package:ecdat R Dataset:mathlevel

609. The Massachusetts Test Score Data Set

name:rdataset-ecdat-mcas reference:rdataset-ecdat-mcas’s home link. R package:ecdat R Dataset:mcas

610. Structure of Demand for Medical Care

name:rdataset-ecdat-medexp reference:rdataset-ecdat-medexp’s home link. R package:ecdat R Dataset:medexp

611. Production for SIC 33

name:rdataset-ecdat-metal reference:rdataset-ecdat-metal’s home link. R package:ecdat R Dataset:metal

612. Inflation and Interest Rates

name:rdataset-ecdat-mishkin reference:rdataset-ecdat-mishkin’s home link. R package:ecdat R Dataset:mishkin

613. Mode Choice

name:rdataset-ecdat-mode reference:rdataset-ecdat-mode’s home link. R package:ecdat R Dataset:mode

614. Data to Study Travel Mode Choice

name:rdataset-ecdat-modechoice reference:rdataset-ecdat-modechoice’s home link. R package:ecdat R Dataset:modechoice

615. International Expansion of U.S. MOFAs (majority-owned Foreign Affiliates in Fire (finance, Insurance and Real Estate)

name:rdataset-ecdat-mofa reference:rdataset-ecdat-mofa’s home link. R package:ecdat R Dataset:mofa

616. Money, GDP and Interest Rate in Canada

name:rdataset-ecdat-money reference:rdataset-ecdat-money’s home link. R package:ecdat R Dataset:money

617. Macroeconomic Series for the United States

name:rdataset-ecdat-moneyus reference:rdataset-ecdat-moneyus’s home link. R package:ecdat R Dataset:moneyus

618. Money, National Product and Interest Rate

name:rdataset-ecdat-mpyr reference:rdataset-ecdat-mpyr’s home link. R package:ecdat R Dataset:mpyr

619. Labor Supply Data

name:rdataset-ecdat-mroz reference:rdataset-ecdat-mroz’s home link. R package:ecdat R Dataset:mroz

620. Municipal Expenditure Data

name:rdataset-ecdat-munexp reference:rdataset-ecdat-munexp’s home link. R package:ecdat R Dataset:munexp

621. Growth of Disposable Income and Treasury Bill Rate

name:rdataset-ecdat-mw reference:rdataset-ecdat-mw’s home link. R package:ecdat R Dataset:mw

622. Willingness to Pay for the Preservation of the Alentejo Natural Park

name:rdataset-ecdat-naturalpark reference:rdataset-ecdat-naturalpark’s home link. R package:ecdat R Dataset:naturalpark

623. Cost Function for Electricity Producers, 1955

name:rdataset-ecdat-nerlove reference:rdataset-ecdat-nerlove’s home link. R package:ecdat R Dataset:nerlove

624. Global Terrorism Database yearly summaries

name:rdataset-ecdat-nkill.bycountryyr reference:rdataset-ecdat-nkill.bycountryyr’s home link. R package:ecdat R Dataset:nkill.bycountryyr

625. Names with Character Set Problems

name:rdataset-ecdat-nonenglishnames reference:rdataset-ecdat-nonenglishnames’s home link. R package:ecdat R Dataset:nonenglishnames

626. Nations with nuclear weapons

name:rdataset-ecdat-nuclearweaponstates reference:rdataset-ecdat-nuclearweaponstates’s home link. R package:ecdat R Dataset:nuclearweaponstates

627. Evolution of occupational distribution in the US

name:rdataset-ecdat-occ1950 reference:rdataset-ecdat-occ1950’s home link. R package:ecdat R Dataset:occ1950

628. Visits to Physician Office

name:rdataset-ecdat-ofp reference:rdataset-ecdat-ofp’s home link. R package:ecdat R Dataset:ofp

629. Oil Investment

name:rdataset-ecdat-oil reference:rdataset-ecdat-oil’s home link. R package:ecdat R Dataset:oil

630. The Orange Juice Data Set

name:rdataset-ecdat-orange reference:rdataset-ecdat-orange’s home link. R package:ecdat R Dataset:orange

631. Labor Force Participation

name:rdataset-ecdat-participation reference:rdataset-ecdat-participation’s home link. R package:ecdat R Dataset:participation

632. Dynamic Relation Between Patents and R&D

name:rdataset-ecdat-patentshgh reference:rdataset-ecdat-patentshgh’s home link. R package:ecdat R Dataset:patentshgh

633. Patents, R&D and Technological Spillovers for a Panel of Firms

name:rdataset-ecdat-patentsrd reference:rdataset-ecdat-patentsrd’s home link. R package:ecdat R Dataset:patentsrd

634. Price and Earnings Index

name:rdataset-ecdat-pe reference:rdataset-ecdat-pe’s home link. R package:ecdat R Dataset:pe

635. Political knowledge in the US and Europe

name:rdataset-ecdat-politicalknowledge reference:rdataset-ecdat-politicalknowledge’s home link. R package:ecdat R Dataset:politicalknowledge

636. Pound-dollar Exchange Rate

name:rdataset-ecdat-pound reference:rdataset-ecdat-pound’s home link. R package:ecdat R Dataset:pound

637. Exchange Rates and Price Indices for France and Italy

name:rdataset-ecdat-ppp reference:rdataset-ecdat-ppp’s home link. R package:ecdat R Dataset:ppp

638. Returns of Size-based Portfolios

name:rdataset-ecdat-pricing reference:rdataset-ecdat-pricing’s home link. R package:ecdat R Dataset:pricing

639. Us States Production

name:rdataset-ecdat-produc reference:rdataset-ecdat-produc’s home link. R package:ecdat R Dataset:produc

640. Panel Survey of Income Dynamics

name:rdataset-ecdat-psid reference:rdataset-ecdat-psid’s home link. R package:ecdat R Dataset:psid

641. Return to Schooling

name:rdataset-ecdat-retschool reference:rdataset-ecdat-retschool’s home link. R package:ecdat R Dataset:retschool

642. Wages and Schooling

name:rdataset-ecdat-schooling reference:rdataset-ecdat-schooling’s home link. R package:ecdat R Dataset:schooling

643. Solow’s Technological Change Data

name:rdataset-ecdat-solow reference:rdataset-ecdat-solow’s home link. R package:ecdat R Dataset:solow

644. Visits to Lake Somerville

name:rdataset-ecdat-somerville reference:rdataset-ecdat-somerville’s home link. R package:ecdat R Dataset:somerville

645. Returns on Standard & Poor’s 500 Index

name:rdataset-ecdat-sp500 reference:rdataset-ecdat-sp500’s home link. R package:ecdat R Dataset:sp500

646. Effects on Learning of Small Class Sizes

name:rdataset-ecdat-star reference:rdataset-ecdat-star’s home link. R package:ecdat R Dataset:star

647. Strike Duration Data

name:rdataset-ecdat-strike reference:rdataset-ecdat-strike’s home link. R package:ecdat R Dataset:strike

648. Strikes Duration

name:rdataset-ecdat-strikedur reference:rdataset-ecdat-strikedur’s home link. R package:ecdat R Dataset:strikedur

649. Number of Strikes in Us Manufacturing

name:rdataset-ecdat-strikenb reference:rdataset-ecdat-strikenb’s home link. R package:ecdat R Dataset:strikenb

650. The Penn Table

name:rdataset-ecdat-sumhes reference:rdataset-ecdat-sumhes’s home link. R package:ecdat R Dataset:sumhes

651. Interest Rate, GDP and Inflation

name:rdataset-ecdat-tbrate reference:rdataset-ecdat-tbrate’s home link. R package:ecdat R Dataset:tbrate

652. Global Terrorism Database yearly summaries

name:rdataset-ecdat-terrorism reference:rdataset-ecdat-terrorism’s home link. R package:ecdat R Dataset:terrorism

653. Households Tobacco Budget Share

name:rdataset-ecdat-tobacco reference:rdataset-ecdat-tobacco’s home link. R package:ecdat R Dataset:tobacco

654. Stated Preferences for Train Traveling

name:rdataset-ecdat-train reference:rdataset-ecdat-train’s home link. R package:ecdat R Dataset:train

655. Statewide Data on Transportation Equipment Manufacturing

name:rdataset-ecdat-transpeq reference:rdataset-ecdat-transpeq’s home link. R package:ecdat R Dataset:transpeq

656. Evaluating Treatment Effect of Training on Earnings

name:rdataset-ecdat-treatment reference:rdataset-ecdat-treatment’s home link. R package:ecdat R Dataset:treatment

657. Choice of Brand for Tuna

name:rdataset-ecdat-tuna reference:rdataset-ecdat-tuna’s home link. R package:ecdat R Dataset:tuna

658. Unemployment Duration

name:rdataset-ecdat-unempdur reference:rdataset-ecdat-unempdur’s home link. R package:ecdat R Dataset:unempdur

659. Unemployment Duration

name:rdataset-ecdat-unemployment reference:rdataset-ecdat-unemployment’s home link. R package:ecdat R Dataset:unemployment

660. Provision of University Teaching and Research

name:rdataset-ecdat-university reference:rdataset-ecdat-university’s home link. R package:ecdat R Dataset:university

661. Official Secrecy of the United States Government

name:rdataset-ecdat-usclassifieddocuments reference:rdataset-ecdat-usclassifieddocuments’s home link. R package:ecdat R Dataset:usclassifieddocuments

662. US Finance Industry Profits

name:rdataset-ecdat-usfinanceindustry reference:rdataset-ecdat-usfinanceindustry’s home link. R package:ecdat R Dataset:usfinanceindustry

663. US GDP per capita with presidents and wars

name:rdataset-ecdat-usgdppresidents reference:rdataset-ecdat-usgdppresidents’s home link. R package:ecdat R Dataset:usgdppresidents

664. Standard abbreviations for states of the United States

name:rdataset-ecdat-usstateabbreviations reference:rdataset-ecdat-usstateabbreviations’s home link. R package:ecdat R Dataset:usstateabbreviations

665. Number of Words in US Tax Law

name:rdataset-ecdat-ustaxwords reference:rdataset-ecdat-ustaxwords’s home link. R package:ecdat R Dataset:ustaxwords

666. Medical Expenses in Vietnam (household Level)

name:rdataset-ecdat-vietnamh reference:rdataset-ecdat-vietnamh’s home link. R package:ecdat R Dataset:vietnamh

667. Medical Expenses in Vietnam (individual Level)

name:rdataset-ecdat-vietnami reference:rdataset-ecdat-vietnami’s home link. R package:ecdat R Dataset:vietnami

668. Panel Data of Individual Wages

name:rdataset-ecdat-wages reference:rdataset-ecdat-wages’s home link. R package:ecdat R Dataset:wages

669. Wages, Experience and Schooling

name:rdataset-ecdat-wages1 reference:rdataset-ecdat-wages1’s home link. R package:ecdat R Dataset:wages1

670. Wife Working Hours

name:rdataset-ecdat-workinghours reference:rdataset-ecdat-workinghours’s home link. R package:ecdat R Dataset:workinghours

671. Yen-dollar Exchange Rate

name:rdataset-ecdat-yen reference:rdataset-ecdat-yen’s home link. R package:ecdat R Dataset:yen

672. Choice of Brand for Yogurts

name:rdataset-ecdat-yogurt reference:rdataset-ecdat-yogurt’s home link. R package:ecdat R Dataset:yogurt

673. Daily Log Returns on BMW Share Price

name:rdataset-evir-bmw reference:rdataset-evir-bmw’s home link. R package:evir R Dataset:bmw

674. Danish Fire Insurance Claims

name:rdataset-evir-danish reference:rdataset-evir-danish’s home link. R package:evir R Dataset:danish

675. The River Nidd Data

name:rdataset-evir-nidd.annual reference:rdataset-evir-nidd.annual’s home link. R package:evir R Dataset:nidd.annual

676. The River Nidd Data

name:rdataset-evir-nidd.thresh reference:rdataset-evir-nidd.thresh’s home link. R package:evir R Dataset:nidd.thresh

677. Daily Log Returns on Siemens Share Price

name:rdataset-evir-siemens reference:rdataset-evir-siemens’s home link. R package:evir R Dataset:siemens

678. SP Data to June 1993

name:rdataset-evir-sp.raw reference:rdataset-evir-sp.raw’s home link. R package:evir R Dataset:sp.raw

679. SP Return Data to October 1987

name:rdataset-evir-spto87 reference:rdataset-evir-spto87’s home link. R package:evir R Dataset:spto87

680. Australian monthly gas production

name:rdataset-forecast-gas reference:rdataset-forecast-gas’s home link. R package:forecast R Dataset:gas

681. Daily morning gold prices

name:rdataset-forecast-gold reference:rdataset-forecast-gold’s home link. R package:forecast R Dataset:gold

682. Half-hourly electricity demand

name:rdataset-forecast-taylor reference:rdataset-forecast-taylor’s home link. R package:forecast R Dataset:taylor

683. Australian total wine sales

name:rdataset-forecast-wineind reference:rdataset-forecast-wineind’s home link. R package:forecast R Dataset:wineind

684. Quarterly production of woollen yarn in Australia

name:rdataset-forecast-woolyrnq reference:rdataset-forecast-woolyrnq’s home link. R package:forecast R Dataset:woolyrnq

685. Monthly anti-diabetic drug subsidy in Australia from 1991 to 2008.

name:rdataset-fpp2-a10 reference:rdataset-fpp2-a10’s home link. R package:fpp2 R Dataset:a10

686. International Arrivals to Australia

name:rdataset-fpp2-arrivals reference:rdataset-fpp2-arrivals’s home link. R package:fpp2 R Dataset:arrivals

687. Air Transport Passengers Australia

name:rdataset-fpp2-ausair reference:rdataset-fpp2-ausair’s home link. R package:fpp2 R Dataset:ausair

688. Quarterly Australian Beer production

name:rdataset-fpp2-ausbeer reference:rdataset-fpp2-ausbeer’s home link. R package:fpp2 R Dataset:ausbeer

689. Monthly expenditure on eating out in Australia

name:rdataset-fpp2-auscafe reference:rdataset-fpp2-auscafe’s home link. R package:fpp2 R Dataset:auscafe

690. International visitors to Australia

name:rdataset-fpp2-austa reference:rdataset-fpp2-austa’s home link. R package:fpp2 R Dataset:austa

691. International Tourists to Australia: Total visitor nights.

name:rdataset-fpp2-austourists reference:rdataset-fpp2-austourists’s home link. R package:fpp2 R Dataset:austourists

692. Call volume for a large North American bank

name:rdataset-fpp2-calls reference:rdataset-fpp2-calls’s home link. R package:fpp2 R Dataset:calls

693. Retail debit card usage in Iceland.

name:rdataset-fpp2-debitcards reference:rdataset-fpp2-debitcards’s home link. R package:fpp2 R Dataset:debitcards

694. Total monthly departures from Australia

name:rdataset-fpp2-departures reference:rdataset-fpp2-departures’s home link. R package:fpp2 R Dataset:departures

695. Half-hourly and daily electricity demand for Victoria, Australia, in 2014

name:rdataset-fpp2-elecdaily reference:rdataset-fpp2-elecdaily’s home link. R package:fpp2 R Dataset:elecdaily

696. Half-hourly and daily electricity demand for Victoria, Australia, in 2014

name:rdataset-fpp2-elecdemand reference:rdataset-fpp2-elecdemand’s home link. R package:fpp2 R Dataset:elecdemand

697. Electrical equipment manufactured in the Euro area.

name:rdataset-fpp2-elecequip reference:rdataset-fpp2-elecequip’s home link. R package:fpp2 R Dataset:elecequip

698. Electricity sales to residential customers in South Australia.

name:rdataset-fpp2-elecsales reference:rdataset-fpp2-elecsales’s home link. R package:fpp2 R Dataset:elecsales

699. Quarterly retail trade: Euro area.

name:rdataset-fpp2-euretail reference:rdataset-fpp2-euretail’s home link. R package:fpp2 R Dataset:euretail

700. US finished motor gasoline product supplied.

name:rdataset-fpp2-gasoline reference:rdataset-fpp2-gasoline’s home link. R package:fpp2 R Dataset:gasoline

701. Daily closing stock prices of Google Inc

name:rdataset-fpp2-goog reference:rdataset-fpp2-goog’s home link. R package:fpp2 R Dataset:goog

702. Daily closing stock prices of Google Inc

name:rdataset-fpp2-goog200 reference:rdataset-fpp2-goog200’s home link. R package:fpp2 R Dataset:goog200

703. Rice production (Guinea)

name:rdataset-fpp2-guinearice reference:rdataset-fpp2-guinearice’s home link. R package:fpp2 R Dataset:guinearice

704. Monthly corticosteroid drug subsidy in Australia from 1991 to 2008.

name:rdataset-fpp2-h02 reference:rdataset-fpp2-h02’s home link. R package:fpp2 R Dataset:h02

705. Daily pageviews for the Hyndsight blog. 30 April 2014 to 29 April 2015.

name:rdataset-fpp2-hyndsight reference:rdataset-fpp2-hyndsight’s home link. R package:fpp2 R Dataset:hyndsight

706. Insurance quotations and advertising expenditure.

name:rdataset-fpp2-insurance reference:rdataset-fpp2-insurance’s home link. R package:fpp2 R Dataset:insurance

707. Livestock (sheep) in Asia, 1961-2007.

name:rdataset-fpp2-livestock reference:rdataset-fpp2-livestock’s home link. R package:fpp2 R Dataset:livestock

708. Boston marathon winning times since 1897

name:rdataset-fpp2-marathon reference:rdataset-fpp2-marathon’s home link. R package:fpp2 R Dataset:marathon

709. Maximum annual temperatures at Moorabbin Airport, Melbourne

name:rdataset-fpp2-maxtemp reference:rdataset-fpp2-maxtemp’s home link. R package:fpp2 R Dataset:maxtemp

710. Total weekly air passenger numbers on Ansett airline flights between Melbourne and Sydney, 1987-1992.

name:rdataset-fpp2-melsyd reference:rdataset-fpp2-melsyd’s home link. R package:fpp2 R Dataset:melsyd

711. Winning times in Olympic men’s 400m track final. 1896-2016.

name:rdataset-fpp2-mens400 reference:rdataset-fpp2-mens400’s home link. R package:fpp2 R Dataset:mens400

712. Annual oil production in Saudi Arabia

name:rdataset-fpp2-oil reference:rdataset-fpp2-oil’s home link. R package:fpp2 R Dataset:oil

713. prison

name:rdataset-fpp2-prison reference:rdataset-fpp2-prison’s home link. R package:fpp2 R Dataset:prison

714. prison

name:rdataset-fpp2-prisonlf reference:rdataset-fpp2-prisonlf’s home link. R package:fpp2 R Dataset:prisonlf

715. Quarterly Australian Electricity production

name:rdataset-fpp2-qauselec reference:rdataset-fpp2-qauselec’s home link. R package:fpp2 R Dataset:qauselec

716. Quarterly Australian Portland Cement production

name:rdataset-fpp2-qcement reference:rdataset-fpp2-qcement’s home link. R package:fpp2 R Dataset:qcement

717. Quarterly Australian Gas Production

name:rdataset-fpp2-qgas reference:rdataset-fpp2-qgas’s home link. R package:fpp2 R Dataset:qgas

718. Annual average sunspot area (1875-2015)

name:rdataset-fpp2-sunspotarea reference:rdataset-fpp2-sunspotarea’s home link. R package:fpp2 R Dataset:sunspotarea

719. Growth rates of personal consumption and personal income in the USA.

name:rdataset-fpp2-uschange reference:rdataset-fpp2-uschange’s home link. R package:fpp2 R Dataset:uschange

720. Electricity monthly total net generation. January 1973 - June 2013.

name:rdataset-fpp2-usmelec reference:rdataset-fpp2-usmelec’s home link. R package:fpp2 R Dataset:usmelec

721. Quarterly visitor nights for various regions of Australia.

name:rdataset-fpp2-visnights reference:rdataset-fpp2-visnights’s home link. R package:fpp2 R Dataset:visnights

722. Annual female murder rate (per 100,000 standard population) in the USA. 1950-2004.

name:rdataset-fpp2-wmurders reference:rdataset-fpp2-wmurders’s home link. R package:fpp2 R Dataset:wmurders

723. Internal functions for gap

name:rdataset-gap-aldh2 reference:rdataset-gap-aldh2’s home link. R package:gap R Dataset:aldh2

724. Internal functions for gap

name:rdataset-gap-apoeapoc reference:rdataset-gap-apoeapoc’s home link. R package:gap R Dataset:apoeapoc

725. Internal functions for gap

name:rdataset-gap-cf reference:rdataset-gap-cf’s home link. R package:gap R Dataset:cf

726. Internal functions for gap

name:rdataset-gap-cnv reference:rdataset-gap-cnv’s home link. R package:gap R Dataset:cnv

727. Internal functions for gap

name:rdataset-gap-crohn reference:rdataset-gap-crohn’s home link. R package:gap R Dataset:crohn

728. Internal functions for gap

name:rdataset-gap-fa reference:rdataset-gap-fa’s home link. R package:gap R Dataset:fa

729. Internal functions for gap

name:rdataset-gap-fsnps reference:rdataset-gap-fsnps’s home link. R package:gap R Dataset:fsnps

730. Internal functions for gap

name:rdataset-gap-hla reference:rdataset-gap-hla’s home link. R package:gap R Dataset:hla

731. Internal functions for gap

name:rdataset-gap-inf1 reference:rdataset-gap-inf1’s home link. R package:gap R Dataset:inf1

732. Internal functions for gap

name:rdataset-gap-jma.cojo reference:rdataset-gap-jma.cojo’s home link. R package:gap R Dataset:jma.cojo

733. Internal functions for gap

name:rdataset-gap-l51 reference:rdataset-gap-l51’s home link. R package:gap R Dataset:l51

734. Internal functions for gap

name:rdataset-gap-lukas reference:rdataset-gap-lukas’s home link. R package:gap R Dataset:lukas

735. Internal functions for gap

name:rdataset-gap-mao reference:rdataset-gap-mao’s home link. R package:gap R Dataset:mao

736. Internal functions for gap

name:rdataset-gap-meyer reference:rdataset-gap-meyer’s home link. R package:gap R Dataset:meyer

737. Internal functions for gap

name:rdataset-gap-mfblong reference:rdataset-gap-mfblong’s home link. R package:gap R Dataset:mfblong

738. Internal functions for gap

name:rdataset-gap-mr reference:rdataset-gap-mr’s home link. R package:gap R Dataset:mr

739. Internal functions for gap

name:rdataset-gap-nep499 reference:rdataset-gap-nep499’s home link. R package:gap R Dataset:nep499

740. Internal functions for gap

name:rdataset-gap-pd reference:rdataset-gap-pd’s home link. R package:gap R Dataset:pd

741. Growth curves of pigs in a 3x3 factorial experiment

name:rdataset-geepack-dietox reference:rdataset-geepack-dietox’s home link. R package:geepack R Dataset:dietox

742. Ordinal Data from Koch

name:rdataset-geepack-koch reference:rdataset-geepack-koch’s home link. R package:geepack R Dataset:koch

743. Data on Obesity from the Muscatine Coronary Risk Factor Study.

name:rdataset-geepack-muscatine reference:rdataset-geepack-muscatine’s home link. R package:geepack R Dataset:muscatine

744. Ohio Children Wheeze Status

name:rdataset-geepack-ohio reference:rdataset-geepack-ohio’s home link. R package:geepack R Dataset:ohio

745. Clustered Ordinal Respiratory Disorder

name:rdataset-geepack-respdis reference:rdataset-geepack-respdis’s home link. R package:geepack R Dataset:respdis

746. Data from a clinical trial comparing two treatments for a respiratory illness

name:rdataset-geepack-respiratory reference:rdataset-geepack-respiratory’s home link. R package:geepack R Dataset:respiratory

747. Epiliptic Seizures

name:rdataset-geepack-seizure reference:rdataset-geepack-seizure’s home link. R package:geepack R Dataset:seizure

748. Growth of Sitka Spruce Trees

name:rdataset-geepack-sitka89 reference:rdataset-geepack-sitka89’s home link. R package:geepack R Dataset:sitka89

749. Log-size of 79 Sitka spruce trees

name:rdataset-geepack-spruce reference:rdataset-geepack-spruce’s home link. R package:geepack R Dataset:spruce

750. Prices of over 50,000 round cut diamonds

name:rdataset-ggplot2-diamonds reference:rdataset-ggplot2-diamonds’s home link. R package:ggplot2 R Dataset:diamonds

751. US economic time series

name:rdataset-ggplot2-economics reference:rdataset-ggplot2-economics’s home link. R package:ggplot2 R Dataset:economics

752. US economic time series

name:rdataset-ggplot2-economics_long reference:rdataset-ggplot2-economics_long’s home link. R package:ggplot2 R Dataset:economics_long

753. 2d density estimate of Old Faithful data

name:rdataset-ggplot2-faithfuld reference:rdataset-ggplot2-faithfuld’s home link. R package:ggplot2 R Dataset:faithfuld

754. ‘colors()’ in Luv space

name:rdataset-ggplot2-luv_colours reference:rdataset-ggplot2-luv_colours’s home link. R package:ggplot2 R Dataset:luv_colours

755. Midwest demographics

name:rdataset-ggplot2-midwest reference:rdataset-ggplot2-midwest’s home link. R package:ggplot2 R Dataset:midwest

756. Fuel economy data from 1999 to 2008 for 38 popular models of cars

name:rdataset-ggplot2-mpg reference:rdataset-ggplot2-mpg’s home link. R package:ggplot2 R Dataset:mpg

757. An updated and expanded version of the mammals sleep dataset

name:rdataset-ggplot2-msleep reference:rdataset-ggplot2-msleep’s home link. R package:ggplot2 R Dataset:msleep

758. Terms of 11 presidents from Eisenhower to Obama

name:rdataset-ggplot2-presidential reference:rdataset-ggplot2-presidential’s home link. R package:ggplot2 R Dataset:presidential

759. Vector field of seal movements

name:rdataset-ggplot2-seals reference:rdataset-ggplot2-seals’s home link. R package:ggplot2 R Dataset:seals

760. Housing sales in TX

name:rdataset-ggplot2-txhousing reference:rdataset-ggplot2-txhousing’s home link. R package:ggplot2 R Dataset:txhousing

761. Movie information and user ratings from IMDB.com.

name:rdataset-ggplot2movies-movies reference:rdataset-ggplot2movies-movies’s home link. R package:ggplot2movies R Dataset:movies

762. Yearly populations of countries from 1960 to 2017

name:rdataset-gt-countrypops reference:rdataset-gt-countrypops’s home link. R package:gt R Dataset:countrypops

763. A toy example tibble for testing with gt: exibble

name:rdataset-gt-exibble reference:rdataset-gt-exibble’s home link. R package:gt R Dataset:exibble

764. Deluxe automobiles from the 2014-2017 period

name:rdataset-gt-gtcars reference:rdataset-gt-gtcars’s home link. R package:gt R Dataset:gtcars

765. A year of pizza sales from a pizza place

name:rdataset-gt-pizzaplace reference:rdataset-gt-pizzaplace’s home link. R package:gt R Dataset:pizzaplace

766. Daily S&P 500 Index data from 1950 to 2015

name:rdataset-gt-sp500 reference:rdataset-gt-sp500’s home link. R package:gt R Dataset:sp500

767. Twice hourly solar zenith angles by month & latitude

name:rdataset-gt-sza reference:rdataset-gt-sza’s home link. R package:gt R Dataset:sza

768. Arbuthnot’s data on male and female birth ratios in London from 1629-1710.

name:rdataset-histdata-arbuthnot reference:rdataset-histdata-arbuthnot’s home link. R package:histdata R Dataset:arbuthnot

769. La Felicisima Armada

name:rdataset-histdata-armada reference:rdataset-histdata-armada’s home link. R package:histdata R Dataset:armada

770. Bowley’s data on values of British and Irish trade, 1855-1899

name:rdataset-histdata-bowley reference:rdataset-histdata-bowley’s home link. R package:histdata R Dataset:bowley

771. Cavendish’s Determinations of the Density of the Earth

name:rdataset-histdata-cavendish reference:rdataset-histdata-cavendish’s home link. R package:histdata R Dataset:cavendish

772. Chest measurements of Scottish Militiamen

name:rdataset-histdata-chestsizes reference:rdataset-histdata-chestsizes’s home link. R package:histdata R Dataset:chestsizes

773. Chest measurements of Scottish Militiamen

name:rdataset-histdata-cheststigler reference:rdataset-histdata-cheststigler’s home link. R package:histdata R Dataset:cheststigler

774. William Farr’s Data on Cholera in London, 1849

name:rdataset-histdata-cholera reference:rdataset-histdata-cholera’s home link. R package:histdata R Dataset:cholera

775. Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives

name:rdataset-histdata-cushnypeebles reference:rdataset-histdata-cushnypeebles’s home link. R package:histdata R Dataset:cushnypeebles

776. Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives

name:rdataset-histdata-cushnypeeblesn reference:rdataset-histdata-cushnypeeblesn’s home link. R package:histdata R Dataset:cushnypeeblesn

777. Edgeworth’s counts of dactyls in Virgil’s Aeneid

name:rdataset-histdata-dactyl reference:rdataset-histdata-dactyl’s home link. R package:histdata R Dataset:dactyl

778. Elderton and Pearson’s (1910) data on drinking and wages

name:rdataset-histdata-drinkswages reference:rdataset-histdata-drinkswages’s home link. R package:histdata R Dataset:drinkswages

779. Edgeworth’s Data on Death Rates in British Counties

name:rdataset-histdata-edgeworthdeaths reference:rdataset-histdata-edgeworthdeaths’s home link. R package:histdata R Dataset:edgeworthdeaths

780. Waite’s data on Patterns in Fingerprints

name:rdataset-histdata-fingerprints reference:rdataset-histdata-fingerprints’s home link. R package:histdata R Dataset:fingerprints

781. Galton’s data on the heights of parents and their children

name:rdataset-histdata-galton reference:rdataset-histdata-galton’s home link. R package:histdata R Dataset:galton

782. Galton’s data on the heights of parents and their children, by child

name:rdataset-histdata-galtonfamilies reference:rdataset-histdata-galtonfamilies’s home link. R package:histdata R Dataset:galtonfamilies

783. Data from A.-M. Guerry, “Essay on the Moral Statistics of France”

name:rdataset-histdata-guerry reference:rdataset-histdata-guerry’s home link. R package:histdata R Dataset:guerry

784. Halley’s Life Table

name:rdataset-histdata-halleylifetable reference:rdataset-histdata-halleylifetable’s home link. R package:histdata R Dataset:halleylifetable

785. W. Stanley Jevons’ data on numerical discrimination

name:rdataset-histdata-jevons reference:rdataset-histdata-jevons’s home link. R package:histdata R Dataset:jevons

786. van Langren’s Data on Longitude Distance between Toledo and Rome

name:rdataset-histdata-langren.all reference:rdataset-histdata-langren.all’s home link. R package:histdata R Dataset:langren.all

787. van Langren’s Data on Longitude Distance between Toledo and Rome

name:rdataset-histdata-langren1644 reference:rdataset-histdata-langren1644’s home link. R package:histdata R Dataset:langren1644

788. Macdonell’s Data on Height and Finger Length of Criminals, used by Gosset (1908)

name:rdataset-histdata-macdonell reference:rdataset-histdata-macdonell’s home link. R package:histdata R Dataset:macdonell

789. Macdonell’s Data on Height and Finger Length of Criminals, used by Gosset (1908)

name:rdataset-histdata-macdonelldf reference:rdataset-histdata-macdonelldf’s home link. R package:histdata R Dataset:macdonelldf

790. Michelson’s Determinations of the Velocity of Light

name:rdataset-histdata-michelson reference:rdataset-histdata-michelson’s home link. R package:histdata R Dataset:michelson

791. Michelson’s Determinations of the Velocity of Light

name:rdataset-histdata-michelsonsets reference:rdataset-histdata-michelsonsets’s home link. R package:histdata R Dataset:michelsonsets

792. Data from Minard’s famous graphic map of Napoleon’s march on Moscow

name:rdataset-histdata-minard.cities reference:rdataset-histdata-minard.cities’s home link. R package:histdata R Dataset:minard.cities

793. Data from Minard’s famous graphic map of Napoleon’s march on Moscow

name:rdataset-histdata-minard.temp reference:rdataset-histdata-minard.temp’s home link. R package:histdata R Dataset:minard.temp

794. Data from Minard’s famous graphic map of Napoleon’s march on Moscow

name:rdataset-histdata-minard.troops reference:rdataset-histdata-minard.troops’s home link. R package:histdata R Dataset:minard.troops

795. Florence Nightingale’s data on deaths from various causes in the Crimean War

name:rdataset-histdata-nightingale reference:rdataset-histdata-nightingale’s home link. R package:histdata R Dataset:nightingale

796. Latitudes and Longitudes of 39 Points in 11 Old Maps

name:rdataset-histdata-oldmaps reference:rdataset-histdata-oldmaps’s home link. R package:histdata R Dataset:oldmaps

797. Pearson and Lee’s data on the heights of parents and children classified by gender

name:rdataset-histdata-pearsonlee reference:rdataset-histdata-pearsonlee’s home link. R package:histdata R Dataset:pearsonlee

798. Polio Field Trials Data

name:rdataset-histdata-poliotrials reference:rdataset-histdata-poliotrials’s home link. R package:histdata R Dataset:poliotrials

799. Parent-Duchatelet’s time-series data on the number of prostitutes in Paris

name:rdataset-histdata-prostitutes reference:rdataset-histdata-prostitutes’s home link. R package:histdata R Dataset:prostitutes

800. Trial of the Pyx

name:rdataset-histdata-pyx reference:rdataset-histdata-pyx’s home link. R package:histdata R Dataset:pyx

801. Statistics of Deadly Quarrels

name:rdataset-histdata-quarrels reference:rdataset-histdata-quarrels’s home link. R package:histdata R Dataset:quarrels

802. John Snow’s Map and Data on the 1854 London Cholera Outbreak

name:rdataset-histdata-snow.dates reference:rdataset-histdata-snow.dates’s home link. R package:histdata R Dataset:snow.dates

803. John Snow’s Map and Data on the 1854 London Cholera Outbreak

name:rdataset-histdata-snow.deaths reference:rdataset-histdata-snow.deaths’s home link. R package:histdata R Dataset:snow.deaths

804. John Snow’s Map and Data on the 1854 London Cholera Outbreak

name:rdataset-histdata-snow.deaths2 reference:rdataset-histdata-snow.deaths2’s home link. R package:histdata R Dataset:snow.deaths2

805. John Snow’s Map and Data on the 1854 London Cholera Outbreak

name:rdataset-histdata-snow.pumps reference:rdataset-histdata-snow.pumps’s home link. R package:histdata R Dataset:snow.pumps

806. John Snow’s Map and Data on the 1854 London Cholera Outbreak

name:rdataset-histdata-snow.streets reference:rdataset-histdata-snow.streets’s home link. R package:histdata R Dataset:snow.streets

807. John F. W. Herschel’s Data on the Orbit of the Twin Stars gamma _Virginis_

name:rdataset-histdata-virginis reference:rdataset-histdata-virginis’s home link. R package:histdata R Dataset:virginis

808. John F. W. Herschel’s Data on the Orbit of the Twin Stars gamma _Virginis_

name:rdataset-histdata-virginis.interp reference:rdataset-histdata-virginis.interp’s home link. R package:histdata R Dataset:virginis.interp

809. Playfair’s Data on Wages and the Price of Wheat

name:rdataset-histdata-wheat reference:rdataset-histdata-wheat’s home link. R package:histdata R Dataset:wheat

810. Playfair’s Data on Wages and the Price of Wheat

name:rdataset-histdata-wheat.monarchs reference:rdataset-histdata-wheat.monarchs’s home link. R package:histdata R Dataset:wheat.monarchs

811. Student’s (1906) Yeast Cell Counts

name:rdataset-histdata-yeast reference:rdataset-histdata-yeast’s home link. R package:histdata R Dataset:yeast

812. Student’s (1906) Yeast Cell Counts

name:rdataset-histdata-yeastd.mat reference:rdataset-histdata-yeastd.mat’s home link. R package:histdata R Dataset:yeastd.mat

813. Darwin’s Heights of Cross- and Self-fertilized Zea May Pairs

name:rdataset-histdata-zeamays reference:rdataset-histdata-zeamays’s home link. R package:histdata R Dataset:zeamays

814. Methylprednisolone data

name:rdataset-hlmdiag-ahd reference:rdataset-hlmdiag-ahd’s home link. R package:hlmdiag R Dataset:ahd

815. Autism data

name:rdataset-hlmdiag-autism reference:rdataset-hlmdiag-autism’s home link. R package:hlmdiag R Dataset:autism

816. Radon data

name:rdataset-hlmdiag-radon reference:rdataset-hlmdiag-radon’s home link. R package:hlmdiag R Dataset:radon

817. Wages for male high school dropouts

name:rdataset-hlmdiag-wages reference:rdataset-hlmdiag-wages’s home link. R package:hlmdiag R Dataset:wages

818. Total Body Composision Data

name:rdataset-hsaur-agefat reference:rdataset-hsaur-agefat’s home link. R package:hsaur R Dataset:agefat

819. Aspirin Data

name:rdataset-hsaur-aspirin reference:rdataset-hsaur-aspirin’s home link. R package:hsaur R Dataset:aspirin

820. BCG Vaccine Data

name:rdataset-hsaur-bcg reference:rdataset-hsaur-bcg’s home link. R package:hsaur R Dataset:bcg

821. Birth and Death Rates Data

name:rdataset-hsaur-birthdeathrates reference:rdataset-hsaur-birthdeathrates’s home link. R package:hsaur R Dataset:birthdeathrates

822. Bladder Cancer Data

name:rdataset-hsaur-bladdercancer reference:rdataset-hsaur-bladdercancer’s home link. R package:hsaur R Dataset:bladdercancer

823. Beat the Blues Data

name:rdataset-hsaur-btheb reference:rdataset-hsaur-btheb’s home link. R package:hsaur R Dataset:btheb

824. Cloud Seeding Data

name:rdataset-hsaur-clouds reference:rdataset-hsaur-clouds’s home link. R package:hsaur R Dataset:clouds

825. CYG OB1 Star Cluster Data

name:rdataset-hsaur-cygob1 reference:rdataset-hsaur-cygob1’s home link. R package:hsaur R Dataset:cygob1

826. Epilepsy Data

name:rdataset-hsaur-epilepsy reference:rdataset-hsaur-epilepsy’s home link. R package:hsaur R Dataset:epilepsy

827. The Forbes 2000 Ranking of the World’s Biggest Companies (Year 2004)

name:rdataset-hsaur-forbes2000 reference:rdataset-hsaur-forbes2000’s home link. R package:hsaur R Dataset:forbes2000

828. Foster Feeding Experiment

name:rdataset-hsaur-foster reference:rdataset-hsaur-foster’s home link. R package:hsaur R Dataset:foster

829. General Health Questionnaire

name:rdataset-hsaur-ghq reference:rdataset-hsaur-ghq’s home link. R package:hsaur R Dataset:ghq

830. Olympic Heptathlon Seoul 1988

name:rdataset-hsaur-heptathlon reference:rdataset-hsaur-heptathlon’s home link. R package:hsaur R Dataset:heptathlon

831. Prevention of Gastointestinal Damages

name:rdataset-hsaur-lanza reference:rdataset-hsaur-lanza’s home link. R package:hsaur R Dataset:lanza

832. Survival Times after Mastectomy of Breast Cancer Patients

name:rdataset-hsaur-mastectomy reference:rdataset-hsaur-mastectomy’s home link. R package:hsaur R Dataset:mastectomy

833. Meteorological Measurements for 11 Years

name:rdataset-hsaur-meteo reference:rdataset-hsaur-meteo’s home link. R package:hsaur R Dataset:meteo

834. Oral Lesions in Rural India

name:rdataset-hsaur-orallesions reference:rdataset-hsaur-orallesions’s home link. R package:hsaur R Dataset:orallesions

835. Phosphate Level Data

name:rdataset-hsaur-phosphate reference:rdataset-hsaur-phosphate’s home link. R package:hsaur R Dataset:phosphate

836. Piston Rings Failures

name:rdataset-hsaur-pistonrings reference:rdataset-hsaur-pistonrings’s home link. R package:hsaur R Dataset:pistonrings

837. Exoplanets Data

name:rdataset-hsaur-planets reference:rdataset-hsaur-planets’s home link. R package:hsaur R Dataset:planets

838. Blood Screening Data

name:rdataset-hsaur-plasma reference:rdataset-hsaur-plasma’s home link. R package:hsaur R Dataset:plasma

839. Familial Andenomatous Polyposis

name:rdataset-hsaur-polyps reference:rdataset-hsaur-polyps’s home link. R package:hsaur R Dataset:polyps

840. Familial Andenomatous Polyposis

name:rdataset-hsaur-polyps3 reference:rdataset-hsaur-polyps3’s home link. R package:hsaur R Dataset:polyps3

841. Romano-British Pottery Data

name:rdataset-hsaur-pottery reference:rdataset-hsaur-pottery’s home link. R package:hsaur R Dataset:pottery

842. Rearrests of Juvenile Felons

name:rdataset-hsaur-rearrests reference:rdataset-hsaur-rearrests’s home link. R package:hsaur R Dataset:rearrests

843. Respiratory Illness Data

name:rdataset-hsaur-respiratory reference:rdataset-hsaur-respiratory’s home link. R package:hsaur R Dataset:respiratory

844. Students Estimates of Lecture Room Width

name:rdataset-hsaur-roomwidth reference:rdataset-hsaur-roomwidth’s home link. R package:hsaur R Dataset:roomwidth

845. Age of Onset of Schizophrenia Data

name:rdataset-hsaur-schizophrenia reference:rdataset-hsaur-schizophrenia’s home link. R package:hsaur R Dataset:schizophrenia

846. Schizophrenia Data

name:rdataset-hsaur-schizophrenia2 reference:rdataset-hsaur-schizophrenia2’s home link. R package:hsaur R Dataset:schizophrenia2

847. Days not Spent at School

name:rdataset-hsaur-schooldays reference:rdataset-hsaur-schooldays’s home link. R package:hsaur R Dataset:schooldays

848. Egyptian Skulls

name:rdataset-hsaur-skulls reference:rdataset-hsaur-skulls’s home link. R package:hsaur R Dataset:skulls

849. Nicotine Gum and Smoking Cessation

name:rdataset-hsaur-smoking reference:rdataset-hsaur-smoking’s home link. R package:hsaur R Dataset:smoking

850. Student Risk Taking

name:rdataset-hsaur-students reference:rdataset-hsaur-students’s home link. R package:hsaur R Dataset:students

851. Crowd Baiting Behaviour and Suicides

name:rdataset-hsaur-suicides reference:rdataset-hsaur-suicides’s home link. R package:hsaur R Dataset:suicides

852. Toothpaste Data

name:rdataset-hsaur-toothpaste reference:rdataset-hsaur-toothpaste’s home link. R package:hsaur R Dataset:toothpaste

853. House of Representatives Voting Data

name:rdataset-hsaur-voting reference:rdataset-hsaur-voting’s home link. R package:hsaur R Dataset:voting

854. Mortality and Water Hardness

name:rdataset-hsaur-water reference:rdataset-hsaur-water’s home link. R package:hsaur R Dataset:water

855. Water Voles Data

name:rdataset-hsaur-watervoles reference:rdataset-hsaur-watervoles’s home link. R package:hsaur R Dataset:watervoles

856. Electricity from Wave Power at Sea

name:rdataset-hsaur-waves reference:rdataset-hsaur-waves’s home link. R package:hsaur R Dataset:waves

857. Gain in Weight of Rats

name:rdataset-hsaur-weightgain reference:rdataset-hsaur-weightgain’s home link. R package:hsaur R Dataset:weightgain

858. Womens Role in Society

name:rdataset-hsaur-womensrole reference:rdataset-hsaur-womensrole’s home link. R package:hsaur R Dataset:womensrole

859. Observed genotype frequencies at MN and S loci, for 2 populations

name:rdataset-hwde-indianirish reference:rdataset-hwde-indianirish’s home link. R package:hwde R Dataset:indianirish

860. Mendel’s F2 trifactorial data for seed shape (A: round or wrinkled), cotyledon color (B: albumen yellow or green), and seed coat color (C: grey-brown or white)

name:rdataset-hwde-mendelabc reference:rdataset-hwde-mendelabc’s home link. R package:hwde R Dataset:mendelabc

861. Auto Data Set

name:rdataset-islr-auto reference:rdataset-islr-auto’s home link. R package:islr R Dataset:auto

862. The Insurance Company (TIC) Benchmark

name:rdataset-islr-caravan reference:rdataset-islr-caravan’s home link. R package:islr R Dataset:caravan

863. Sales of Child Car Seats

name:rdataset-islr-carseats reference:rdataset-islr-carseats’s home link. R package:islr R Dataset:carseats

864. U.S. News and World Report’s College Data

name:rdataset-islr-college reference:rdataset-islr-college’s home link. R package:islr R Dataset:college

865. Credit Card Balance Data

name:rdataset-islr-credit reference:rdataset-islr-credit’s home link. R package:islr R Dataset:credit

866. Credit Card Default Data

name:rdataset-islr-default reference:rdataset-islr-default’s home link. R package:islr R Dataset:default

867. Baseball Data

name:rdataset-islr-hitters reference:rdataset-islr-hitters’s home link. R package:islr R Dataset:hitters

868. NCI 60 Data

name:rdataset-islr-nci60 reference:rdataset-islr-nci60’s home link. R package:islr R Dataset:nci60

869. Orange Juice Data

name:rdataset-islr-oj reference:rdataset-islr-oj’s home link. R package:islr R Dataset:oj

870. Portfolio Data

name:rdataset-islr-portfolio reference:rdataset-islr-portfolio’s home link. R package:islr R Dataset:portfolio

871. S&P Stock Market Data

name:rdataset-islr-smarket reference:rdataset-islr-smarket’s home link. R package:islr R Dataset:smarket

872. Mid-Atlantic Wage Data

name:rdataset-islr-wage reference:rdataset-islr-wage’s home link. R package:islr R Dataset:wage

873. Weekly S&P Stock Market Data

name:rdataset-islr-weekly reference:rdataset-islr-weekly’s home link. R package:islr R Dataset:weekly

874. Raw EEG data, single trial, 50Hz.

name:rdataset-itsadug-eeg reference:rdataset-itsadug-eeg’s home link. R package:itsadug R Dataset:eeg

875. Simulated time series data.

name:rdataset-itsadug-simdat reference:rdataset-itsadug-simdat’s home link. R package:itsadug R Dataset:simdat

876. data from Section 1.19

name:rdataset-kmsurv-aids reference:rdataset-kmsurv-aids’s home link. R package:kmsurv R Dataset:aids

877. data from Section 1.9

name:rdataset-kmsurv-alloauto reference:rdataset-kmsurv-alloauto’s home link. R package:kmsurv R Dataset:alloauto

878. data from Exercise 13.1, p418

name:rdataset-kmsurv-allograft reference:rdataset-kmsurv-allograft’s home link. R package:kmsurv R Dataset:allograft

879. data from Exercise 4.7, p122

name:rdataset-kmsurv-azt reference:rdataset-kmsurv-azt’s home link. R package:kmsurv R Dataset:azt

880. data from Exercise 5.8, p147

name:rdataset-kmsurv-baboon reference:rdataset-kmsurv-baboon’s home link. R package:kmsurv R Dataset:baboon

881. data from Section 1.18

name:rdataset-kmsurv-bcdeter reference:rdataset-kmsurv-bcdeter’s home link. R package:kmsurv R Dataset:bcdeter

882. data from Section 1.14

name:rdataset-kmsurv-bfeed reference:rdataset-kmsurv-bfeed’s home link. R package:kmsurv R Dataset:bfeed

883. data from Section 1.3

name:rdataset-kmsurv-bmt reference:rdataset-kmsurv-bmt’s home link. R package:kmsurv R Dataset:bmt

884. data from Exercise 7.7, p223

name:rdataset-kmsurv-bnct reference:rdataset-kmsurv-bnct’s home link. R package:kmsurv R Dataset:bnct

885. data from Section 1.5

name:rdataset-kmsurv-btrial reference:rdataset-kmsurv-btrial’s home link. R package:kmsurv R Dataset:btrial

886. data from Section 1.6

name:rdataset-kmsurv-burn reference:rdataset-kmsurv-burn’s home link. R package:kmsurv R Dataset:burn

887. data from Section 1.16

name:rdataset-kmsurv-channing reference:rdataset-kmsurv-channing’s home link. R package:kmsurv R Dataset:channing

888. data from Section 1.2

name:rdataset-kmsurv-drug6mp reference:rdataset-kmsurv-drug6mp’s home link. R package:kmsurv R Dataset:drug6mp

889. data from Exercise 7.6, p222

name:rdataset-kmsurv-drughiv reference:rdataset-kmsurv-drughiv’s home link. R package:kmsurv R Dataset:drughiv

890. data from Section 1.10

name:rdataset-kmsurv-hodg reference:rdataset-kmsurv-hodg’s home link. R package:kmsurv R Dataset:hodg

891. data from Section 1.4

name:rdataset-kmsurv-kidney reference:rdataset-kmsurv-kidney’s home link. R package:kmsurv R Dataset:kidney

892. Data on 38 individuals using a kidney dialysis machine

name:rdataset-kmsurv-kidrecurr reference:rdataset-kmsurv-kidrecurr’s home link. R package:kmsurv R Dataset:kidrecurr

893. data from Section 1.7

name:rdataset-kmsurv-kidtran reference:rdataset-kmsurv-kidtran’s home link. R package:kmsurv R Dataset:kidtran

894. data from Section 1.8

name:rdataset-kmsurv-larynx reference:rdataset-kmsurv-larynx’s home link. R package:kmsurv R Dataset:larynx

895. data from Exercise 4.4, p120

name:rdataset-kmsurv-lung reference:rdataset-kmsurv-lung’s home link. R package:kmsurv R Dataset:lung

896. data from Section 1.13

name:rdataset-kmsurv-pneumon reference:rdataset-kmsurv-pneumon’s home link. R package:kmsurv R Dataset:pneumon

897. data from Section 1.15

name:rdataset-kmsurv-psych reference:rdataset-kmsurv-psych’s home link. R package:kmsurv R Dataset:psych

898. data from Exercise 7.13, p225

name:rdataset-kmsurv-rats reference:rdataset-kmsurv-rats’s home link. R package:kmsurv R Dataset:rats

899. data from Section 1.12

name:rdataset-kmsurv-std reference:rdataset-kmsurv-std’s home link. R package:kmsurv R Dataset:std

900. data from Exercise 5.6, p146

name:rdataset-kmsurv-stddiag reference:rdataset-kmsurv-stddiag’s home link. R package:kmsurv R Dataset:stddiag

901. data from Section 1.11

name:rdataset-kmsurv-tongue reference:rdataset-kmsurv-tongue’s home link. R package:kmsurv R Dataset:tongue

902. data from Exercise 7.14, p225

name:rdataset-kmsurv-twins reference:rdataset-kmsurv-twins’s home link. R package:kmsurv R Dataset:twins

903. Yield data from a Minnesota barley trial

name:rdataset-lattice-barley reference:rdataset-lattice-barley’s home link. R package:lattice R Dataset:barley

904. Atmospheric environmental conditions in New York City

name:rdataset-lattice-environmental reference:rdataset-lattice-environmental’s home link. R package:lattice R Dataset:environmental

905. Engine exhaust fumes from burning ethanol

name:rdataset-lattice-ethanol reference:rdataset-lattice-ethanol’s home link. R package:lattice R Dataset:ethanol

906. Melanoma skin cancer incidence

name:rdataset-lattice-melanoma reference:rdataset-lattice-melanoma’s home link. R package:lattice R Dataset:melanoma

907. Heights of New York Choral Society singers

name:rdataset-lattice-singer reference:rdataset-lattice-singer’s home link. R package:lattice R Dataset:singer

908. Mortality Rates in US by Cause and Gender

name:rdataset-lattice-usmortality reference:rdataset-lattice-usmortality’s home link. R package:lattice R Dataset:usmortality

909. Mortality Rates in US by Cause and Gender

name:rdataset-lattice-usregionalmortality reference:rdataset-lattice-usregionalmortality’s home link. R package:lattice R Dataset:usregionalmortality

910. Arabidopsis clipping/fertilization data

name:rdataset-lme4-arabidopsis reference:rdataset-lme4-arabidopsis’s home link. R package:lme4 R Dataset:arabidopsis

911. Breakage Angle of Chocolate Cakes

name:rdataset-lme4-cake reference:rdataset-lme4-cake’s home link. R package:lme4 R Dataset:cake

912. Contagious bovine pleuropneumonia

name:rdataset-lme4-cbpp reference:rdataset-lme4-cbpp’s home link. R package:lme4 R Dataset:cbpp

913. Yield of dyestuff by batch

name:rdataset-lme4-dyestuff reference:rdataset-lme4-dyestuff’s home link. R package:lme4 R Dataset:dyestuff

914. Yield of dyestuff by batch

name:rdataset-lme4-dyestuff2 reference:rdataset-lme4-dyestuff2’s home link. R package:lme4 R Dataset:dyestuff2

915. Data on red grouse ticks from Elston et al. 2001

name:rdataset-lme4-grouseticks reference:rdataset-lme4-grouseticks’s home link. R package:lme4 R Dataset:grouseticks

916. University Lecture/Instructor Evaluations by Students at ETH

name:rdataset-lme4-insteval reference:rdataset-lme4-insteval’s home link. R package:lme4 R Dataset:insteval

917. Paste strength by batch and cask

name:rdataset-lme4-pastes reference:rdataset-lme4-pastes’s home link. R package:lme4 R Dataset:pastes

918. Variation in penicillin testing

name:rdataset-lme4-penicillin reference:rdataset-lme4-penicillin’s home link. R package:lme4 R Dataset:penicillin

919. Reaction times in a sleep deprivation study

name:rdataset-lme4-sleepstudy reference:rdataset-lme4-sleepstudy’s home link. R package:lme4 R Dataset:sleepstudy

920. Verbal Aggression item responses

name:rdataset-lme4-verbagg reference:rdataset-lme4-verbagg’s home link. R package:lme4 R Dataset:verbagg

921. Data set for Unstructured Treatment Interruption Study

name:rdataset-lmec-utidata reference:rdataset-lmec-utidata’s home link. R package:lmec R Dataset:utidata

922. Determinations of Nickel Content

name:rdataset-mass-abbey reference:rdataset-mass-abbey’s home link. R package:mass R Dataset:abbey

923. Accidental Deaths in the US 1973-1978

name:rdataset-mass-accdeaths reference:rdataset-mass-accdeaths’s home link. R package:mass R Dataset:accdeaths

924. Australian AIDS Survival Data

name:rdataset-mass-aids2 reference:rdataset-mass-aids2’s home link. R package:mass R Dataset:aids2

925. Brain and Body Weights for 28 Species

name:rdataset-mass-animals reference:rdataset-mass-animals’s home link. R package:mass R Dataset:animals

926. Anorexia Data on Weight Change

name:rdataset-mass-anorexia reference:rdataset-mass-anorexia’s home link. R package:mass R Dataset:anorexia

927. Presence of Bacteria after Drug Treatments

name:rdataset-mass-bacteria reference:rdataset-mass-bacteria’s home link. R package:mass R Dataset:bacteria

928. Body Temperature Series of Beaver 1

name:rdataset-mass-beav1 reference:rdataset-mass-beav1’s home link. R package:mass R Dataset:beav1

929. Body Temperature Series of Beaver 2

name:rdataset-mass-beav2 reference:rdataset-mass-beav2’s home link. R package:mass R Dataset:beav2

930. Biopsy Data on Breast Cancer Patients

name:rdataset-mass-biopsy reference:rdataset-mass-biopsy’s home link. R package:mass R Dataset:biopsy

931. Risk Factors Associated with Low Infant Birth Weight

name:rdataset-mass-birthwt reference:rdataset-mass-birthwt’s home link. R package:mass R Dataset:birthwt

932. Housing Values in Suburbs of Boston

name:rdataset-mass-boston reference:rdataset-mass-boston’s home link. R package:mass R Dataset:boston

933. Data from a cabbage field trial

name:rdataset-mass-cabbages reference:rdataset-mass-cabbages’s home link. R package:mass R Dataset:cabbages

934. Colours of Eyes and Hair of People in Caithness

name:rdataset-mass-caith reference:rdataset-mass-caith’s home link. R package:mass R Dataset:caith

935. Data from 93 Cars on Sale in the USA in 1993

name:rdataset-mass-cars93 reference:rdataset-mass-cars93’s home link. R package:mass R Dataset:cars93

936. Anatomical Data from Domestic Cats

name:rdataset-mass-cats reference:rdataset-mass-cats’s home link. R package:mass R Dataset:cats

937. Heat Evolved by Setting Cements

name:rdataset-mass-cement reference:rdataset-mass-cement’s home link. R package:mass R Dataset:cement

938. Copper in Wholemeal Flour

name:rdataset-mass-chem reference:rdataset-mass-chem’s home link. R package:mass R Dataset:chem

939. Co-operative Trial in Analytical Chemistry

name:rdataset-mass-coop reference:rdataset-mass-coop’s home link. R package:mass R Dataset:coop

940. Performance of Computer CPUs

name:rdataset-mass-cpus reference:rdataset-mass-cpus’s home link. R package:mass R Dataset:cpus

941. Morphological Measurements on Leptograpsus Crabs

name:rdataset-mass-crabs reference:rdataset-mass-crabs’s home link. R package:mass R Dataset:crabs

942. Diagnostic Tests on Patients with Cushing’s Syndrome

name:rdataset-mass-cushings reference:rdataset-mass-cushings’s home link. R package:mass R Dataset:cushings

943. DDT in Kale

name:rdataset-mass-ddt reference:rdataset-mass-ddt’s home link. R package:mass R Dataset:ddt

944. Monthly Deaths from Lung Diseases in the UK

name:rdataset-mass-deaths reference:rdataset-mass-deaths’s home link. R package:mass R Dataset:deaths

945. Deaths of Car Drivers in Great Britain 1969-84

name:rdataset-mass-drivers reference:rdataset-mass-drivers’s home link. R package:mass R Dataset:drivers

946. Foraging Ecology of Bald Eagles

name:rdataset-mass-eagles reference:rdataset-mass-eagles’s home link. R package:mass R Dataset:eagles

947. Seizure Counts for Epileptics

name:rdataset-mass-epil reference:rdataset-mass-epil’s home link. R package:mass R Dataset:epil

948. Ecological Factors in Farm Management

name:rdataset-mass-farms reference:rdataset-mass-farms’s home link. R package:mass R Dataset:farms

949. Measurements of Forensic Glass Fragments

name:rdataset-mass-fgl reference:rdataset-mass-fgl’s home link. R package:mass R Dataset:fgl

950. Forbes’ Data on Boiling Points in the Alps

name:rdataset-mass-forbes reference:rdataset-mass-forbes’s home link. R package:mass R Dataset:forbes

951. Level of GAG in Urine of Children

name:rdataset-mass-gagurine reference:rdataset-mass-gagurine’s home link. R package:mass R Dataset:gagurine

952. Velocities for 82 Galaxies

name:rdataset-mass-galaxies reference:rdataset-mass-galaxies’s home link. R package:mass R Dataset:galaxies

953. Remission Times of Leukaemia Patients

name:rdataset-mass-gehan reference:rdataset-mass-gehan’s home link. R package:mass R Dataset:gehan

954. Rat Genotype Data

name:rdataset-mass-genotype reference:rdataset-mass-genotype’s home link. R package:mass R Dataset:genotype

955. Old Faithful Geyser Data

name:rdataset-mass-geyser reference:rdataset-mass-geyser’s home link. R package:mass R Dataset:geyser

956. Line Transect of Soil in Gilgai Territory

name:rdataset-mass-gilgais reference:rdataset-mass-gilgais’s home link. R package:mass R Dataset:gilgais

957. Record Times in Scottish Hill Races

name:rdataset-mass-hills reference:rdataset-mass-hills’s home link. R package:mass R Dataset:hills

958. Frequency Table from a Copenhagen Housing Conditions Survey

name:rdataset-mass-housing reference:rdataset-mass-housing’s home link. R package:mass R Dataset:housing

959. Yields from a Barley Field Trial

name:rdataset-mass-immer reference:rdataset-mass-immer’s home link. R package:mass R Dataset:immer

960. Numbers of Car Insurance claims

name:rdataset-mass-insurance reference:rdataset-mass-insurance’s home link. R package:mass R Dataset:insurance

961. Survival Times and White Blood Counts for Leukaemia Patients

name:rdataset-mass-leuk reference:rdataset-mass-leuk’s home link. R package:mass R Dataset:leuk

962. Brain and Body Weights for 62 Species of Land Mammals

name:rdataset-mass-mammals reference:rdataset-mass-mammals’s home link. R package:mass R Dataset:mammals

963. Data from a Simulated Motorcycle Accident

name:rdataset-mass-mcycle reference:rdataset-mass-mcycle’s home link. R package:mass R Dataset:mcycle

964. Survival from Malignant Melanoma

name:rdataset-mass-melanoma reference:rdataset-mass-melanoma’s home link. R package:mass R Dataset:melanoma

965. Age of Menarche in Warsaw

name:rdataset-mass-menarche reference:rdataset-mass-menarche’s home link. R package:mass R Dataset:menarche

966. Michelson’s Speed of Light Data

name:rdataset-mass-michelson reference:rdataset-mass-michelson’s home link. R package:mass R Dataset:michelson

967. Minnesota High School Graduates of 1938

name:rdataset-mass-minn38 reference:rdataset-mass-minn38’s home link. R package:mass R Dataset:minn38

968. Accelerated Life Testing of Motorettes

name:rdataset-mass-motors reference:rdataset-mass-motors’s home link. R package:mass R Dataset:motors

969. Effect of Calcium Chloride on Muscle Contraction in Rat Hearts

name:rdataset-mass-muscle reference:rdataset-mass-muscle’s home link. R package:mass R Dataset:muscle

970. Newcomb’s Measurements of the Passage Time of Light

name:rdataset-mass-newcomb reference:rdataset-mass-newcomb’s home link. R package:mass R Dataset:newcomb

971. Eighth-Grade Pupils in the Netherlands

name:rdataset-mass-nlschools reference:rdataset-mass-nlschools’s home link. R package:mass R Dataset:nlschools

972. Classical N, P, K Factorial Experiment

name:rdataset-mass-npk reference:rdataset-mass-npk’s home link. R package:mass R Dataset:npk

973. US Naval Petroleum Reserve No. 1 data

name:rdataset-mass-npr1 reference:rdataset-mass-npr1’s home link. R package:mass R Dataset:npr1

974. Data from an Oats Field Trial

name:rdataset-mass-oats reference:rdataset-mass-oats’s home link. R package:mass R Dataset:oats

975. Tests of Auditory Perception in Children with OME

name:rdataset-mass-ome reference:rdataset-mass-ome’s home link. R package:mass R Dataset:ome

976. The Painter’s Data of de Piles

name:rdataset-mass-painters reference:rdataset-mass-painters’s home link. R package:mass R Dataset:painters

977. N. L. Prater’s Petrol Refinery Data

name:rdataset-mass-petrol reference:rdataset-mass-petrol’s home link. R package:mass R Dataset:petrol

978. Belgium Phone Calls 1950-1973

name:rdataset-mass-phones reference:rdataset-mass-phones’s home link. R package:mass R Dataset:phones

979. Diabetes in Pima Indian Women

name:rdataset-mass-pima.te reference:rdataset-mass-pima.te’s home link. R package:mass R Dataset:pima.te

980. Diabetes in Pima Indian Women

name:rdataset-mass-pima.tr reference:rdataset-mass-pima.tr’s home link. R package:mass R Dataset:pima.tr

981. Diabetes in Pima Indian Women

name:rdataset-mass-pima.tr2 reference:rdataset-mass-pima.tr2’s home link. R package:mass R Dataset:pima.tr2

982. Absenteeism from School in Rural New South Wales

name:rdataset-mass-quine reference:rdataset-mass-quine’s home link. R package:mass R Dataset:quine

983. Blood Pressure in Rabbits

name:rdataset-mass-rabbit reference:rdataset-mass-rabbit’s home link. R package:mass R Dataset:rabbit

984. Road Accident Deaths in US States

name:rdataset-mass-road reference:rdataset-mass-road’s home link. R package:mass R Dataset:road

985. Numbers of Rotifers by Fluid Density

name:rdataset-mass-rotifer reference:rdataset-mass-rotifer’s home link. R package:mass R Dataset:rotifer

986. Accelerated Testing of Tyre Rubber

name:rdataset-mass-rubber reference:rdataset-mass-rubber’s home link. R package:mass R Dataset:rubber

987. Ships Damage Data

name:rdataset-mass-ships reference:rdataset-mass-ships’s home link. R package:mass R Dataset:ships

988. Shoe wear data of Box, Hunter and Hunter

name:rdataset-mass-shoes reference:rdataset-mass-shoes’s home link. R package:mass R Dataset:shoes

989. Percentage of Shrimp in Shrimp Cocktail

name:rdataset-mass-shrimp reference:rdataset-mass-shrimp’s home link. R package:mass R Dataset:shrimp

990. Space Shuttle Autolander Problem

name:rdataset-mass-shuttle reference:rdataset-mass-shuttle’s home link. R package:mass R Dataset:shuttle

991. Growth Curves for Sitka Spruce Trees in 1988

name:rdataset-mass-sitka reference:rdataset-mass-sitka’s home link. R package:mass R Dataset:sitka

992. Growth Curves for Sitka Spruce Trees in 1989

name:rdataset-mass-sitka89 reference:rdataset-mass-sitka89’s home link. R package:mass R Dataset:sitka89

993. AFM Compositions of Aphyric Skye Lavas

name:rdataset-mass-skye reference:rdataset-mass-skye’s home link. R package:mass R Dataset:skye

994. Snail Mortality Data

name:rdataset-mass-snails reference:rdataset-mass-snails’s home link. R package:mass R Dataset:snails

995. Returns of the Standard and Poors 500

name:rdataset-mass-sp500 reference:rdataset-mass-sp500’s home link. R package:mass R Dataset:sp500

996. The Saturated Steam Pressure Data

name:rdataset-mass-steam reference:rdataset-mass-steam’s home link. R package:mass R Dataset:steam

997. The Stormer Viscometer Data

name:rdataset-mass-stormer reference:rdataset-mass-stormer’s home link. R package:mass R Dataset:stormer

998. Student Survey Data

name:rdataset-mass-survey reference:rdataset-mass-survey’s home link. R package:mass R Dataset:survey

999. Synthetic Classification Problem

name:rdataset-mass-synth.te reference:rdataset-mass-synth.te’s home link. R package:mass R Dataset:synth.te

1000. Synthetic Classification Problem

name:rdataset-mass-synth.tr reference:rdataset-mass-synth.tr’s home link. R package:mass R Dataset:synth.tr

1001. Spatial Topographic Data

name:rdataset-mass-topo reference:rdataset-mass-topo’s home link. R package:mass R Dataset:topo

1002. Effect of Swedish Speed Limits on Accidents

name:rdataset-mass-traffic reference:rdataset-mass-traffic’s home link. R package:mass R Dataset:traffic

1003. Nutritional and Marketing Information on US Cereals

name:rdataset-mass-uscereal reference:rdataset-mass-uscereal’s home link. R package:mass R Dataset:uscereal

1004. The Effect of Punishment Regimes on Crime Rates

name:rdataset-mass-uscrime reference:rdataset-mass-uscrime’s home link. R package:mass R Dataset:uscrime

1005. Veteran’s Administration Lung Cancer Trial

name:rdataset-mass-va reference:rdataset-mass-va’s home link. R package:mass R Dataset:va

1006. Counts of Waders at 15 Sites in South Africa

name:rdataset-mass-waders reference:rdataset-mass-waders’s home link. R package:mass R Dataset:waders

1007. House Insulation: Whiteside’s Data

name:rdataset-mass-whiteside reference:rdataset-mass-whiteside’s home link. R package:mass R Dataset:whiteside

1008. Weight Loss Data from an Obese Patient

name:rdataset-mass-wtloss reference:rdataset-mass-wtloss’s home link. R package:mass R Dataset:wtloss

1009. Example Data for the Design Functions

name:rdataset-mediation-boundsdata reference:rdataset-mediation-boundsdata’s home link. R package:mediation R Dataset:boundsdata

1010. Example Data for the Crossover Encouragement Design

name:rdataset-mediation-ceddata reference:rdataset-mediation-ceddata’s home link. R package:mediation R Dataset:ceddata

1011. Brader, Valentino and Suhay (2008) Framing Experiment Data

name:rdataset-mediation-framing reference:rdataset-mediation-framing’s home link. R package:mediation R Dataset:framing

1012. JOBS II data

name:rdataset-mediation-jobs reference:rdataset-mediation-jobs’s home link. R package:mediation R Dataset:jobs

1013. School-level data

name:rdataset-mediation-school reference:rdataset-mediation-school’s home link. R package:mediation R Dataset:school

1014. Hypothetical student-level data

name:rdataset-mediation-student reference:rdataset-mediation-student’s home link. R package:mediation R Dataset:student

1015. Subset of variables from the CHAIN project

name:rdataset-mi-chain reference:rdataset-mi-chain’s home link. R package:mi R Dataset:chain

1016. National Longitudinal Survey of Youth Extract

name:rdataset-mi-nlsyv reference:rdataset-mi-nlsyv’s home link. R package:mi R Dataset:nlsyv

1017. Alcohol Consumption per Capita

name:rdataset-mosaicdata-alcohol reference:rdataset-mosaicdata-alcohol’s home link. R package:mosaicdata R Dataset:alcohol

1018. US Births in 1969 - 1988

name:rdataset-mosaicdata-birthdays reference:rdataset-mosaicdata-birthdays’s home link. R package:mosaicdata R Dataset:birthdays

1019. US Births

name:rdataset-mosaicdata-births reference:rdataset-mosaicdata-births’s home link. R package:mosaicdata R Dataset:births

1020. US Births in 2015

name:rdataset-mosaicdata-births2015 reference:rdataset-mosaicdata-births2015’s home link. R package:mosaicdata R Dataset:births2015

1021. US Births in 1978

name:rdataset-mosaicdata-births78 reference:rdataset-mosaicdata-births78’s home link. R package:mosaicdata R Dataset:births78

1022. Standard Deck of Cards

name:rdataset-mosaicdata-cards reference:rdataset-mosaicdata-cards’s home link. R package:mosaicdata R Dataset:cards

1023. CoolingWater

name:rdataset-mosaicdata-coolingwater reference:rdataset-mosaicdata-coolingwater’s home link. R package:mosaicdata R Dataset:coolingwater

1024. Countries

name:rdataset-mosaicdata-countries reference:rdataset-mosaicdata-countries’s home link. R package:mosaicdata R Dataset:countries

1025. Data from the 1985 Current Population Survey (CPS85)

name:rdataset-mosaicdata-cps85 reference:rdataset-mosaicdata-cps85’s home link. R package:mosaicdata R Dataset:cps85

1026. Weight of dimes

name:rdataset-mosaicdata-dimes reference:rdataset-mosaicdata-dimes’s home link. R package:mosaicdata R Dataset:dimes

1027. Galton’s dataset of parent and child heights

name:rdataset-mosaicdata-galton reference:rdataset-mosaicdata-galton’s home link. R package:mosaicdata R Dataset:galton

1028. Data from the Child Health and Development Studies

name:rdataset-mosaicdata-gestation reference:rdataset-mosaicdata-gestation’s home link. R package:mosaicdata R Dataset:gestation

1029. Goose Permit Study

name:rdataset-mosaicdata-goosepermits reference:rdataset-mosaicdata-goosepermits’s home link. R package:mosaicdata R Dataset:goosepermits

1030. Data from a heat exchanger laboratory

name:rdataset-mosaicdata-heatx reference:rdataset-mosaicdata-heatx’s home link. R package:mosaicdata R Dataset:heatx

1031. Health Evaluation and Linkage to Primary Care

name:rdataset-mosaicdata-helpfull reference:rdataset-mosaicdata-helpfull’s home link. R package:mosaicdata R Dataset:helpfull

1032. Health Evaluation and Linkage to Primary Care

name:rdataset-mosaicdata-helpmiss reference:rdataset-mosaicdata-helpmiss’s home link. R package:mosaicdata R Dataset:helpmiss

1033. Health Evaluation and Linkage to Primary Care

name:rdataset-mosaicdata-helprct reference:rdataset-mosaicdata-helprct’s home link. R package:mosaicdata R Dataset:helprct

1034. Foot measurements in children

name:rdataset-mosaicdata-kidsfeet reference:rdataset-mosaicdata-kidsfeet’s home link. R package:mosaicdata R Dataset:kidsfeet

1035. Marriage records

name:rdataset-mosaicdata-marriage reference:rdataset-mosaicdata-marriage’s home link. R package:mosaicdata R Dataset:marriage

1036. Mites and Wilt Disease

name:rdataset-mosaicdata-mites reference:rdataset-mosaicdata-mites’s home link. R package:mosaicdata R Dataset:mites

1037. Volume of Users of a Rail Trail

name:rdataset-mosaicdata-railtrail reference:rdataset-mosaicdata-railtrail’s home link. R package:mosaicdata R Dataset:railtrail

1038. Volume of Users of a Massachusetts Rail Trail

name:rdataset-mosaicdata-riders reference:rdataset-mosaicdata-riders’s home link. R package:mosaicdata R Dataset:riders

1039. Houses in Saratoga County (2006)

name:rdataset-mosaicdata-saratogahouses reference:rdataset-mosaicdata-saratogahouses’s home link. R package:mosaicdata R Dataset:saratogahouses

1040. State by State SAT data

name:rdataset-mosaicdata-sat reference:rdataset-mosaicdata-sat’s home link. R package:mosaicdata R Dataset:sat

1041. Snowfall data for Grand Rapids, MI

name:rdataset-mosaicdata-snowgr reference:rdataset-mosaicdata-snowgr’s home link. R package:mosaicdata R Dataset:snowgr

1042. 100 m Swimming World Records

name:rdataset-mosaicdata-swimrecords reference:rdataset-mosaicdata-swimrecords’s home link. R package:mosaicdata R Dataset:swimrecords

1043. Cherry Blossom Race

name:rdataset-mosaicdata-tenmilerace reference:rdataset-mosaicdata-tenmilerace’s home link. R package:mosaicdata R Dataset:tenmilerace

1044. Utility bills

name:rdataset-mosaicdata-utilities reference:rdataset-mosaicdata-utilities’s home link. R package:mosaicdata R Dataset:utilities

1045. Utility bills

name:rdataset-mosaicdata-utilities2 reference:rdataset-mosaicdata-utilities2’s home link. R package:mosaicdata R Dataset:utilities2

1046. Weather

name:rdataset-mosaicdata-weather reference:rdataset-mosaicdata-weather’s home link. R package:mosaicdata R Dataset:weather

1047. Data from the Whickham survey

name:rdataset-mosaicdata-whickham reference:rdataset-mosaicdata-whickham’s home link. R package:mosaicdata R Dataset:whickham

1048. Data from the Amsterdam Cohort Studies on HIV infection and AIDS

name:rdataset-mstate-aidssi reference:rdataset-mstate-aidssi’s home link. R package:mstate R Dataset:aidssi

1049. Data from the Amsterdam Cohort Studies on HIV infection and AIDS

name:rdataset-mstate-aidssi2 reference:rdataset-mstate-aidssi2’s home link. R package:mstate R Dataset:aidssi2

1050. BMT data from Klein and Moeschberger

name:rdataset-mstate-bmt reference:rdataset-mstate-bmt’s home link. R package:mstate R Dataset:bmt

1051. Data from the European Society for Blood and Marrow Transplantation (EBMT)

name:rdataset-mstate-ebmt1 reference:rdataset-mstate-ebmt1’s home link. R package:mstate R Dataset:ebmt1

1052. Data from the European Society for Blood and Marrow Transplantation (EBMT)

name:rdataset-mstate-ebmt2 reference:rdataset-mstate-ebmt2’s home link. R package:mstate R Dataset:ebmt2

1053. Data from the European Society for Blood and Marrow Transplantation (EBMT)

name:rdataset-mstate-ebmt3 reference:rdataset-mstate-ebmt3’s home link. R package:mstate R Dataset:ebmt3

1054. Data from the European Society for Blood and Marrow Transplantation (EBMT)

name:rdataset-mstate-ebmt4 reference:rdataset-mstate-ebmt4’s home link. R package:mstate R Dataset:ebmt4

1055. Abnormal prothrombin levels in liver cirrhosis

name:rdataset-mstate-prothr reference:rdataset-mstate-prothr’s home link. R package:mstate R Dataset:prothr

1056. Rheumatoid Arthritis Clinical Trial

name:rdataset-multgee-arthritis reference:rdataset-multgee-arthritis’s home link. R package:multgee R Dataset:arthritis

1057. Homeless Data

name:rdataset-multgee-housing reference:rdataset-multgee-housing’s home link. R package:multgee R Dataset:housing

1058. Airline names.

name:rdataset-nycflights13-airlines reference:rdataset-nycflights13-airlines’s home link. R package:nycflights13 R Dataset:airlines

1059. Airport metadata

name:rdataset-nycflights13-airports reference:rdataset-nycflights13-airports’s home link. R package:nycflights13 R Dataset:airports

1060. Flights data

name:rdataset-nycflights13-flights reference:rdataset-nycflights13-flights’s home link. R package:nycflights13 R Dataset:flights

1061. Plane metadata.

name:rdataset-nycflights13-planes reference:rdataset-nycflights13-planes’s home link. R package:nycflights13 R Dataset:planes

1062. Hourly weather data

name:rdataset-nycflights13-weather reference:rdataset-nycflights13-weather’s home link. R package:nycflights13 R Dataset:weather

1063. Absenteeism from school in New South Wales

name:rdataset-openintro-absenteeism reference:rdataset-openintro-absenteeism’s home link. R package:openintro R Dataset:absenteeism

1064. American Community Survey, 2012

name:rdataset-openintro-acs12 reference:rdataset-openintro-acs12’s home link. R package:openintro R Dataset:acs12

1065. Age at first marriage of 5,534 US women.

name:rdataset-openintro-age_at_mar reference:rdataset-openintro-age_at_mar’s home link. R package:openintro R Dataset:age_at_mar

1066. Housing prices in Ames, Iowa

name:rdataset-openintro-ames reference:rdataset-openintro-ames’s home link. R package:openintro R Dataset:ames

1067. Acute Myocardial Infarction (Heart Attack) Events

name:rdataset-openintro-ami_occurrences reference:rdataset-openintro-ami_occurrences’s home link. R package:openintro R Dataset:ami_occurrences

1068. Pre-existing conditions in 92 children

name:rdataset-openintro-antibiotics reference:rdataset-openintro-antibiotics’s home link. R package:openintro R Dataset:antibiotics

1069. Male and female births in London

name:rdataset-openintro-arbuthnot reference:rdataset-openintro-arbuthnot’s home link. R package:openintro R Dataset:arbuthnot

1070. How important is it to ask pointed questions?

name:rdataset-openintro-ask reference:rdataset-openintro-ask’s home link. R package:openintro R Dataset:ask

1071. Simulated data for association plots

name:rdataset-openintro-association reference:rdataset-openintro-association’s home link. R package:openintro R Dataset:association

1072. Eye color of couples

name:rdataset-openintro-assortative_mating reference:rdataset-openintro-assortative_mating’s home link. R package:openintro R Dataset:assortative_mating

1073. Eye color of couples

name:rdataset-openintro-assortive_mating reference:rdataset-openintro-assortive_mating’s home link. R package:openintro R Dataset:assortive_mating

1074. Cardiovascular problems for two types of Diabetes medicines

name:rdataset-openintro-avandia reference:rdataset-openintro-avandia’s home link. R package:openintro R Dataset:avandia

1075. The Child Health and Development Studies

name:rdataset-openintro-babies reference:rdataset-openintro-babies’s home link. R package:openintro R Dataset:babies

1076. Crawling age

name:rdataset-openintro-babies_crawl reference:rdataset-openintro-babies_crawl’s home link. R package:openintro R Dataset:babies_crawl

1077. Beer and blood alcohol content

name:rdataset-openintro-bac reference:rdataset-openintro-bac’s home link. R package:openintro R Dataset:bac

1078. Lifespan of ball bearings

name:rdataset-openintro-ball_bearing reference:rdataset-openintro-ball_bearing’s home link. R package:openintro R Dataset:ball_bearing

1079. Body measurements of 507 physically active individuals.

name:rdataset-openintro-bdims reference:rdataset-openintro-bdims’s home link. R package:openintro R Dataset:bdims

1080. Efficacy of Pfizer-BioNTech COVID-19 vaccine on adolescents

name:rdataset-openintro-biontech_adolescents reference:rdataset-openintro-biontech_adolescents’s home link. R package:openintro R Dataset:biontech_adolescents

1081. Aircraft-Wildlife Collisions

name:rdataset-openintro-birds reference:rdataset-openintro-birds’s home link. R package:openintro R Dataset:birds

1082. North Carolina births, 100 cases

name:rdataset-openintro-births reference:rdataset-openintro-births’s home link. R package:openintro R Dataset:births

1083. US births

name:rdataset-openintro-births14 reference:rdataset-openintro-births14’s home link. R package:openintro R Dataset:births14

1084. Blizzard Employee Voluntary Salary Info.

name:rdataset-openintro-blizzard_salary reference:rdataset-openintro-blizzard_salary’s home link. R package:openintro R Dataset:blizzard_salary

1085. Sample of books on a shelf

name:rdataset-openintro-books reference:rdataset-openintro-books’s home link. R package:openintro R Dataset:books

1086. Burger preferences

name:rdataset-openintro-burger reference:rdataset-openintro-burger’s home link. R package:openintro R Dataset:burger

1087. Cancer in dogs

name:rdataset-openintro-cancer_in_dogs reference:rdataset-openintro-cancer_in_dogs’s home link. R package:openintro R Dataset:cancer_in_dogs

1088. Deck of cards

name:rdataset-openintro-cards reference:rdataset-openintro-cards’s home link. R package:openintro R Dataset:cards

1089. cars93

name:rdataset-openintro-cars93 reference:rdataset-openintro-cars93’s home link. R package:openintro R Dataset:cars93

1090. Community college housing (simulated data)

name:rdataset-openintro-cchousing reference:rdataset-openintro-cchousing’s home link. R package:openintro R Dataset:cchousing

1091. Random sample of 2000 U.S. Census Data

name:rdataset-openintro-census reference:rdataset-openintro-census’s home link. R package:openintro R Dataset:census

1092. Summary information for 31 cherry trees

name:rdataset-openintro-cherry reference:rdataset-openintro-cherry’s home link. R package:openintro R Dataset:cherry

1093. Child care hours

name:rdataset-openintro-china reference:rdataset-openintro-china’s home link. R package:openintro R Dataset:china

1094. CIA Factbook Details on Countries

name:rdataset-openintro-cia_factbook reference:rdataset-openintro-cia_factbook’s home link. R package:openintro R Dataset:cia_factbook

1095. Simulated class data

name:rdataset-openintro-classdata reference:rdataset-openintro-classdata’s home link. R package:openintro R Dataset:classdata

1096. Cleveland and Sacramento

name:rdataset-openintro-cle_sac reference:rdataset-openintro-cle_sac’s home link. R package:openintro R Dataset:cle_sac

1097. Temperature Summary Data, Geography Limited

name:rdataset-openintro-climate70 reference:rdataset-openintro-climate70’s home link. R package:openintro R Dataset:climate70

1098. Climber Drugs Data.

name:rdataset-openintro-climber_drugs reference:rdataset-openintro-climber_drugs’s home link. R package:openintro R Dataset:climber_drugs

1099. Coast Starlight Amtrak train

name:rdataset-openintro-coast_starlight reference:rdataset-openintro-coast_starlight’s home link. R package:openintro R Dataset:coast_starlight

1100. OpenIntro Statistics colors

name:rdataset-openintro-col reference:rdataset-openintro-col’s home link. R package:openintro R Dataset:col

1101. Sample data sets for correlation problems

name:rdataset-openintro-corr_match reference:rdataset-openintro-corr_match’s home link. R package:openintro R Dataset:corr_match

1102. Country ISO information

name:rdataset-openintro-country_iso reference:rdataset-openintro-country_iso’s home link. R package:openintro R Dataset:country_iso

1103. CPR data set

name:rdataset-openintro-cpr reference:rdataset-openintro-cpr’s home link. R package:openintro R Dataset:cpr

1104. CPU’s Released between 2010 and 2020.

name:rdataset-openintro-cpu reference:rdataset-openintro-cpu’s home link. R package:openintro R Dataset:cpu

1105. College credits.

name:rdataset-openintro-credits reference:rdataset-openintro-credits’s home link. R package:openintro R Dataset:credits

1106. Daycare fines

name:rdataset-openintro-daycare_fines reference:rdataset-openintro-daycare_fines’s home link. R package:openintro R Dataset:daycare_fines

1107. Type 2 Diabetes Clinical Trial for Patients 10-17 Years Old

name:rdataset-openintro-diabetes2 reference:rdataset-openintro-diabetes2’s home link. R package:openintro R Dataset:diabetes2

1108. Survey on views of the DREAM Act

name:rdataset-openintro-dream reference:rdataset-openintro-dream’s home link. R package:openintro R Dataset:dream

1109. Quadcopter Drone Blades

name:rdataset-openintro-drone_blades reference:rdataset-openintro-drone_blades’s home link. R package:openintro R Dataset:drone_blades

1110. Drug use of students and parents

name:rdataset-openintro-drug_use reference:rdataset-openintro-drug_use’s home link. R package:openintro R Dataset:drug_use

1111. Sale prices of houses in Duke Forest, Durham, NC

name:rdataset-openintro-duke_forest reference:rdataset-openintro-duke_forest’s home link. R package:openintro R Dataset:duke_forest

1112. Earthquakes

name:rdataset-openintro-earthquakes reference:rdataset-openintro-earthquakes’s home link. R package:openintro R Dataset:earthquakes

1113. Survey on Ebola quarantine

name:rdataset-openintro-ebola_survey reference:rdataset-openintro-ebola_survey’s home link. R package:openintro R Dataset:ebola_survey

1114. Elmhurst College gift aid

name:rdataset-openintro-elmhurst reference:rdataset-openintro-elmhurst’s home link. R package:openintro R Dataset:elmhurst

1115. Data frame representing information about a collection of emails

name:rdataset-openintro-email reference:rdataset-openintro-email’s home link. R package:openintro R Dataset:email

1116. Data frame representing information about a collection of emails

name:rdataset-openintro-email_test reference:rdataset-openintro-email_test’s home link. R package:openintro R Dataset:email_test

1117. Sample of 50 emails

name:rdataset-openintro-email50 reference:rdataset-openintro-email50’s home link. R package:openintro R Dataset:email50

1118. American Adults on Regulation and Renewable Energy

name:rdataset-openintro-env_regulation reference:rdataset-openintro-env_regulation’s home link. R package:openintro R Dataset:env_regulation

1119. Vehicle info from the EPA for 2012

name:rdataset-openintro-epa2012 reference:rdataset-openintro-epa2012’s home link. R package:openintro R Dataset:epa2012

1120. Vehicle info from the EPA for 2021

name:rdataset-openintro-epa2021 reference:rdataset-openintro-epa2021’s home link. R package:openintro R Dataset:epa2021

1121. Environmental Sustainability Index 2005

name:rdataset-openintro-esi reference:rdataset-openintro-esi’s home link. R package:openintro R Dataset:esi

1122. Ethanol Treatment for Tumors Experiment

name:rdataset-openintro-ethanol reference:rdataset-openintro-ethanol’s home link. R package:openintro R Dataset:ethanol

1123. Professor evaluations and beauty

name:rdataset-openintro-evals reference:rdataset-openintro-evals’s home link. R package:openintro R Dataset:evals

1124. Exam and course grades for statistics students

name:rdataset-openintro-exam_grades reference:rdataset-openintro-exam_grades’s home link. R package:openintro R Dataset:exam_grades

1125. Exam scores

name:rdataset-openintro-exams reference:rdataset-openintro-exams’s home link. R package:openintro R Dataset:exams

1126. Number of Exclusive Relationships

name:rdataset-openintro-exclusive_relationship reference:rdataset-openintro-exclusive_relationship’s home link. R package:openintro R Dataset:exclusive_relationship

1127. Can Americans categorize facts and opinions?

name:rdataset-openintro-fact_opinion reference:rdataset-openintro-fact_opinion’s home link. R package:openintro R Dataset:fact_opinion

1128. Simulated sample of parent / teen college attendance

name:rdataset-openintro-family_college reference:rdataset-openintro-family_college’s home link. R package:openintro R Dataset:family_college

1129. Nutrition in fast food

name:rdataset-openintro-fastfood reference:rdataset-openintro-fastfood’s home link. R package:openintro R Dataset:fastfood

1130. Summary of male heights from USDA Food Commodity Intake Database

name:rdataset-openintro-fcid reference:rdataset-openintro-fcid’s home link. R package:openintro R Dataset:fcid

1131. Female college student heights, in inches

name:rdataset-openintro-fheights reference:rdataset-openintro-fheights’s home link. R package:openintro R Dataset:fheights

1132. Findings on n-3 Fatty Acid Supplement Health Benefits

name:rdataset-openintro-fish_oil_18 reference:rdataset-openintro-fish_oil_18’s home link. R package:openintro R Dataset:fish_oil_18

1133. River flow data

name:rdataset-openintro-flow_rates reference:rdataset-openintro-flow_rates’s home link. R package:openintro R Dataset:flow_rates

1134. Friday the 13th

name:rdataset-openintro-friday reference:rdataset-openintro-friday’s home link. R package:openintro R Dataset:friday

1135. Poll about use of full-body airport scanners

name:rdataset-openintro-full_body_scan reference:rdataset-openintro-full_body_scan’s home link. R package:openintro R Dataset:full_body_scan

1136. GDP Countries Data.

name:rdataset-openintro-gdp_countries reference:rdataset-openintro-gdp_countries’s home link. R package:openintro R Dataset:gdp_countries

1137. Fake data for a gear company example

name:rdataset-openintro-gear_company reference:rdataset-openintro-gear_company’s home link. R package:openintro R Dataset:gear_company

1138. Bank manager recommendations based on gender

name:rdataset-openintro-gender_discrimination reference:rdataset-openintro-gender_discrimination’s home link. R package:openintro R Dataset:gender_discrimination

1139. Get it Dunn Run, Race Times

name:rdataset-openintro-get_it_dunn_run reference:rdataset-openintro-get_it_dunn_run’s home link. R package:openintro R Dataset:get_it_dunn_run

1140. Analytical skills of young gifted children

name:rdataset-openintro-gifted reference:rdataset-openintro-gifted’s home link. R package:openintro R Dataset:gifted

1141. Pew survey on global warming

name:rdataset-openintro-global_warming_pew reference:rdataset-openintro-global_warming_pew’s home link. R package:openintro R Dataset:global_warming_pew

1142. Google stock data

name:rdataset-openintro-goog reference:rdataset-openintro-goog’s home link. R package:openintro R Dataset:goog

1143. Pew Research poll on government approval ratings

name:rdataset-openintro-gov_poll reference:rdataset-openintro-gov_poll’s home link. R package:openintro R Dataset:gov_poll

1144. Survey of Duke students on GPA, studying, and more

name:rdataset-openintro-gpa reference:rdataset-openintro-gpa’s home link. R package:openintro R Dataset:gpa

1145. Sample of students and their GPA and IQ

name:rdataset-openintro-gpa_iq reference:rdataset-openintro-gpa_iq’s home link. R package:openintro R Dataset:gpa_iq

1146. gpa_study_hours

name:rdataset-openintro-gpa_study_hours reference:rdataset-openintro-gpa_study_hours’s home link. R package:openintro R Dataset:gpa_study_hours

1147. Simulated data for analyzing the relationship between watching TV and grades

name:rdataset-openintro-gradestv reference:rdataset-openintro-gradestv’s home link. R package:openintro R Dataset:gradestv

1148. Simulated Google search experiment

name:rdataset-openintro-gsearch reference:rdataset-openintro-gsearch’s home link. R package:openintro R Dataset:gsearch

1149. 2010 General Social Survey

name:rdataset-openintro-gss2010 reference:rdataset-openintro-gss2010’s home link. R package:openintro R Dataset:gss2010

1150. Health Coverage and Health Status

name:rdataset-openintro-health_coverage reference:rdataset-openintro-health_coverage’s home link. R package:openintro R Dataset:health_coverage

1151. Pew Research Center poll on health care, including question variants

name:rdataset-openintro-healthcare_law_survey reference:rdataset-openintro-healthcare_law_survey’s home link. R package:openintro R Dataset:healthcare_law_survey

1152. Heart Transplant Data

name:rdataset-openintro-heart_transplant reference:rdataset-openintro-heart_transplant’s home link. R package:openintro R Dataset:heart_transplant

1153. Helium football

name:rdataset-openintro-helium reference:rdataset-openintro-helium’s home link. R package:openintro R Dataset:helium

1154. Socioeconomic status and reduced-fee school lunches

name:rdataset-openintro-helmet reference:rdataset-openintro-helmet’s home link. R package:openintro R Dataset:helmet

1155. Human Freedom Index

name:rdataset-openintro-hfi reference:rdataset-openintro-hfi’s home link. R package:openintro R Dataset:hfi

1156. United States House of Representatives historical make-up

name:rdataset-openintro-house reference:rdataset-openintro-house’s home link. R package:openintro R Dataset:house

1157. Simulated data set on student housing

name:rdataset-openintro-housing reference:rdataset-openintro-housing’s home link. R package:openintro R Dataset:housing

1158. High School and Beyond survey

name:rdataset-openintro-hsb2 reference:rdataset-openintro-hsb2’s home link. R package:openintro R Dataset:hsb2

1159. Great Britain: husband and wife pairs

name:rdataset-openintro-husbands_wives reference:rdataset-openintro-husbands_wives’s home link. R package:openintro R Dataset:husbands_wives

1160. Poll on illegal workers in the US

name:rdataset-openintro-immigration reference:rdataset-openintro-immigration’s home link. R package:openintro R Dataset:immigration

1161. Introduction to Modern Statistics (IMS) Colors

name:rdataset-openintro-imscol reference:rdataset-openintro-imscol’s home link. R package:openintro R Dataset:imscol

1162. Infant Mortality Rates, 2012

name:rdataset-openintro-infmortrate reference:rdataset-openintro-infmortrate’s home link. R package:openintro R Dataset:infmortrate

1163. Length of songs on an iPod

name:rdataset-openintro-ipod reference:rdataset-openintro-ipod’s home link. R package:openintro R Dataset:ipod

1164. Simulated juror data set

name:rdataset-openintro-jury reference:rdataset-openintro-jury’s home link. R package:openintro R Dataset:jury

1165. Kobe Bryant basketball performance

name:rdataset-openintro-kobe_basket reference:rdataset-openintro-kobe_basket’s home link. R package:openintro R Dataset:kobe_basket

1166. Are Emily and Greg More Employable Than Lakisha and Jamal?

name:rdataset-openintro-labor_market_discrimination reference:rdataset-openintro-labor_market_discrimination’s home link. R package:openintro R Dataset:labor_market_discrimination

1167. Gender, Socioeconomic Class, and Interview Invites

name:rdataset-openintro-law_resume reference:rdataset-openintro-law_resume’s home link. R package:openintro R Dataset:law_resume

1168. Legalization of Marijuana Support in 2010 California Survey

name:rdataset-openintro-leg_mari reference:rdataset-openintro-leg_mari’s home link. R package:openintro R Dataset:leg_mari

1169. Field data on lizards observed in their natural habitat

name:rdataset-openintro-lizard_habitat reference:rdataset-openintro-lizard_habitat’s home link. R package:openintro R Dataset:lizard_habitat

1170. Lizard speeds

name:rdataset-openintro-lizard_run reference:rdataset-openintro-lizard_run’s home link. R package:openintro R Dataset:lizard_run

1171. Loan data from Lending Club

name:rdataset-openintro-loan50 reference:rdataset-openintro-loan50’s home link. R package:openintro R Dataset:loan50

1172. Loan data from Lending Club

name:rdataset-openintro-loans_full_schema reference:rdataset-openintro-loans_full_schema’s home link. R package:openintro R Dataset:loans_full_schema

1173. London Borough Boundaries

name:rdataset-openintro-london_boroughs reference:rdataset-openintro-london_boroughs’s home link. R package:openintro R Dataset:london_boroughs

1174. London Murders, 2006-2011

name:rdataset-openintro-london_murders reference:rdataset-openintro-london_murders’s home link. R package:openintro R Dataset:london_murders

1175. Influence of a Good Mood on Helpfulness

name:rdataset-openintro-mail_me reference:rdataset-openintro-mail_me’s home link. R package:openintro R Dataset:mail_me

1176. Survey of Duke students and the area of their major

name:rdataset-openintro-major_survey reference:rdataset-openintro-major_survey’s home link. R package:openintro R Dataset:major_survey

1177. Malaria Vaccine Trial

name:rdataset-openintro-malaria reference:rdataset-openintro-malaria’s home link. R package:openintro R Dataset:malaria

1178. Sample of 100 male heights

name:rdataset-openintro-male_heights reference:rdataset-openintro-male_heights’s home link. R package:openintro R Dataset:male_heights

1179. Random sample of adult male heights

name:rdataset-openintro-male_heights_fcid reference:rdataset-openintro-male_heights_fcid’s home link. R package:openintro R Dataset:male_heights_fcid

1180. Sleep in Mammals

name:rdataset-openintro-mammals reference:rdataset-openintro-mammals’s home link. R package:openintro R Dataset:mammals

1181. Experiment with Mammogram Randomized

name:rdataset-openintro-mammogram reference:rdataset-openintro-mammogram’s home link. R package:openintro R Dataset:mammogram

1182. New York City Marathon Times (outdated)

name:rdataset-openintro-marathon reference:rdataset-openintro-marathon’s home link. R package:openintro R Dataset:marathon

1183. Wii Mario Kart auctions from Ebay

name:rdataset-openintro-mariokart reference:rdataset-openintro-mariokart’s home link. R package:openintro R Dataset:mariokart

1184. Marvel Cinematic Universe films

name:rdataset-openintro-mcu_films reference:rdataset-openintro-mcu_films’s home link. R package:openintro R Dataset:mcu_films

1185. President’s party performance and unemployment rate

name:rdataset-openintro-midterms_house reference:rdataset-openintro-midterms_house’s home link. R package:openintro R Dataset:midterms_house

1186. Migraines and acupuncture

name:rdataset-openintro-migraine reference:rdataset-openintro-migraine’s home link. R package:openintro R Dataset:migraine

1187. US Military Demographics

name:rdataset-openintro-military reference:rdataset-openintro-military’s home link. R package:openintro R Dataset:military

1188. Salary data for Major League Baseball (2010)

name:rdataset-openintro-mlb reference:rdataset-openintro-mlb’s home link. R package:openintro R Dataset:mlb

1189. Batter Statistics for 2018 Major League Baseball (MLB) Season

name:rdataset-openintro-mlb_players_18 reference:rdataset-openintro-mlb_players_18’s home link. R package:openintro R Dataset:mlb_players_18

1190. Major League Baseball Teams Data.

name:rdataset-openintro-mlb_teams reference:rdataset-openintro-mlb_teams’s home link. R package:openintro R Dataset:mlb_teams

1191. Major League Baseball Player Hitting Statistics for 2010

name:rdataset-openintro-mlbbat10 reference:rdataset-openintro-mlbbat10’s home link. R package:openintro R Dataset:mlbbat10

1192. Minneapolis police use of force data.

name:rdataset-openintro-mn_police_use_of_force reference:rdataset-openintro-mn_police_use_of_force’s home link. R package:openintro R Dataset:mn_police_use_of_force

1193. Medial temporal lobe (MTL) and other data for 26 participants

name:rdataset-openintro-mtl reference:rdataset-openintro-mtl’s home link. R package:openintro R Dataset:mtl

1194. Data for 20 metropolitan areas

name:rdataset-openintro-murders reference:rdataset-openintro-murders’s home link. R package:openintro R Dataset:murders

1195. NBA Player heights from 2008-9

name:rdataset-openintro-nba_heights reference:rdataset-openintro-nba_heights’s home link. R package:openintro R Dataset:nba_heights

1196. NBA Players for the 2018-2019 season

name:rdataset-openintro-nba_players_19 reference:rdataset-openintro-nba_players_19’s home link. R package:openintro R Dataset:nba_players_19

1197. North Carolina births, 1000 cases

name:rdataset-openintro-ncbirths reference:rdataset-openintro-ncbirths’s home link. R package:openintro R Dataset:ncbirths

1198. Nuclear Arms Reduction Survey

name:rdataset-openintro-nuclear_survey reference:rdataset-openintro-nuclear_survey’s home link. R package:openintro R Dataset:nuclear_survey

1199. New York City Marathon Times

name:rdataset-openintro-nyc_marathon reference:rdataset-openintro-nyc_marathon’s home link. R package:openintro R Dataset:nyc_marathon

1200. Flights data

name:rdataset-openintro-nycflights reference:rdataset-openintro-nycflights’s home link. R package:openintro R Dataset:nycflights

1201. California poll on drilling off the California coast

name:rdataset-openintro-offshore_drilling reference:rdataset-openintro-offshore_drilling’s home link. R package:openintro R Dataset:offshore_drilling

1202. OpenIntro colors

name:rdataset-openintro-openintro_colors reference:rdataset-openintro-openintro_colors’s home link. R package:openintro R Dataset:openintro_colors

1203. Opportunity cost of purchases

name:rdataset-openintro-opportunity_cost reference:rdataset-openintro-opportunity_cost’s home link. R package:openintro R Dataset:opportunity_cost

1204. 1986 Challenger disaster and O-rings

name:rdataset-openintro-orings reference:rdataset-openintro-orings’s home link. R package:openintro R Dataset:orings

1205. Oscar winners, 1929 to 2018

name:rdataset-openintro-oscars reference:rdataset-openintro-oscars’s home link. R package:openintro R Dataset:oscars

1206. Simulated data sets for different types of outliers

name:rdataset-openintro-outliers reference:rdataset-openintro-outliers’s home link. R package:openintro R Dataset:outliers

1207. Guesses at the weight of Penelope (a cow)

name:rdataset-openintro-penelope reference:rdataset-openintro-penelope’s home link. R package:openintro R Dataset:penelope

1208. What’s the best way to loosen a rusty bolt?

name:rdataset-openintro-penetrating_oil reference:rdataset-openintro-penetrating_oil’s home link. R package:openintro R Dataset:penetrating_oil

1209. Penny Ages

name:rdataset-openintro-penny_ages reference:rdataset-openintro-penny_ages’s home link. R package:openintro R Dataset:penny_ages

1210. Pew Survey on Energy Sources in 2018

name:rdataset-openintro-pew_energy_2018 reference:rdataset-openintro-pew_energy_2018’s home link. R package:openintro R Dataset:pew_energy_2018

1211. Photo classifications: fashion or not

name:rdataset-openintro-photo_classify reference:rdataset-openintro-photo_classify’s home link. R package:openintro R Dataset:photo_classify

1212. Piracy and PIPA/SOPA

name:rdataset-openintro-piracy reference:rdataset-openintro-piracy’s home link. R package:openintro R Dataset:piracy

1213. Table of Playing Cards in 52-Card Deck

name:rdataset-openintro-playing_cards reference:rdataset-openintro-playing_cards’s home link. R package:openintro R Dataset:playing_cards

1214. Air quality for Durham, NC

name:rdataset-openintro-pm25_2011_durham reference:rdataset-openintro-pm25_2011_durham’s home link. R package:openintro R Dataset:pm25_2011_durham

1215. Poker winnings during 50 sessions

name:rdataset-openintro-poker reference:rdataset-openintro-poker’s home link. R package:openintro R Dataset:poker

1216. Possums in Australia and New Guinea

name:rdataset-openintro-possum reference:rdataset-openintro-possum’s home link. R package:openintro R Dataset:possum

1217. US Poll on who it is better to raise taxes on

name:rdataset-openintro-ppp_201503 reference:rdataset-openintro-ppp_201503’s home link. R package:openintro R Dataset:ppp_201503

1218. Birth counts

name:rdataset-openintro-present reference:rdataset-openintro-present’s home link. R package:openintro R Dataset:present

1219. United States Presidental History

name:rdataset-openintro-president reference:rdataset-openintro-president’s home link. R package:openintro R Dataset:president

1220. Prison isolation experiment

name:rdataset-openintro-prison reference:rdataset-openintro-prison’s home link. R package:openintro R Dataset:prison

1221. User reported fuel efficiency for 2017 Toyota Prius Prime

name:rdataset-openintro-prius_mpg reference:rdataset-openintro-prius_mpg’s home link. R package:openintro R Dataset:prius_mpg

1222. Yahoo! News Race and Justice poll results

name:rdataset-openintro-race_justice reference:rdataset-openintro-race_justice’s home link. R package:openintro R Dataset:race_justice

1223. Reddit Survey on Financial Independence.

name:rdataset-openintro-reddit_finance reference:rdataset-openintro-reddit_finance’s home link. R package:openintro R Dataset:reddit_finance

1224. Simulated data for regression

name:rdataset-openintro-res_demo_1 reference:rdataset-openintro-res_demo_1’s home link. R package:openintro R Dataset:res_demo_1

1225. Simulated data for regression

name:rdataset-openintro-res_demo_2 reference:rdataset-openintro-res_demo_2’s home link. R package:openintro R Dataset:res_demo_2

1226. Which resume attributes drive job callbacks?

name:rdataset-openintro-resume reference:rdataset-openintro-resume’s home link. R package:openintro R Dataset:resume

1227. Sample Responses to Two Public Health Questions

name:rdataset-openintro-rosling_responses reference:rdataset-openintro-rosling_responses’s home link. R package:openintro R Dataset:rosling_responses

1228. Russians’ Opinions on US Election Influence in 2016

name:rdataset-openintro-russian_influence_on_us_election_2016 reference:rdataset-openintro-russian_influence_on_us_election_2016’s home link. R package:openintro R Dataset:russian_influence_on_us_election_2016

1229. Sustainability and Economic Indicators for South Africa.

name:rdataset-openintro-sa_gdp_elec reference:rdataset-openintro-sa_gdp_elec’s home link. R package:openintro R Dataset:sa_gdp_elec

1230. Salinity in Bimini Lagoon, Bahamas

name:rdataset-openintro-salinity reference:rdataset-openintro-salinity’s home link. R package:openintro R Dataset:salinity

1231. Simulated data for SAT score improvement

name:rdataset-openintro-sat_improve reference:rdataset-openintro-sat_improve’s home link. R package:openintro R Dataset:sat_improve

1232. SAT and GPA data

name:rdataset-openintro-satgpa reference:rdataset-openintro-satgpa’s home link. R package:openintro R Dataset:satgpa

1233. Public Opinion with SCOTUS ruling on American Healthcare Act

name:rdataset-openintro-scotus_healthcare reference:rdataset-openintro-scotus_healthcare’s home link. R package:openintro R Dataset:scotus_healthcare

1234. Names of pets in Seattle

name:rdataset-openintro-seattlepets reference:rdataset-openintro-seattlepets’s home link. R package:openintro R Dataset:seattlepets

1235. Bank manager recommendations based on sex

name:rdataset-openintro-sex_discrimination reference:rdataset-openintro-sex_discrimination’s home link. R package:openintro R Dataset:sex_discrimination

1236. Simpson’s Paradox: Covid

name:rdataset-openintro-simpsons_paradox_covid reference:rdataset-openintro-simpsons_paradox_covid’s home link. R package:openintro R Dataset:simpsons_paradox_covid

1237. Simulated data sets, drawn from a normal distribution.

name:rdataset-openintro-simulated_normal reference:rdataset-openintro-simulated_normal’s home link. R package:openintro R Dataset:simulated_normal

1238. Simulated data for sample scatterplots

name:rdataset-openintro-simulated_scatter reference:rdataset-openintro-simulated_scatter’s home link. R package:openintro R Dataset:simulated_scatter

1239. Sinusitis and antibiotic experiment

name:rdataset-openintro-sinusitis reference:rdataset-openintro-sinusitis’s home link. R package:openintro R Dataset:sinusitis

1240. Survey on sleep deprivation and transportation workers

name:rdataset-openintro-sleep_deprivation reference:rdataset-openintro-sleep_deprivation’s home link. R package:openintro R Dataset:sleep_deprivation

1241. Smallpox vaccine results

name:rdataset-openintro-smallpox reference:rdataset-openintro-smallpox’s home link. R package:openintro R Dataset:smallpox

1242. UK Smoking Data

name:rdataset-openintro-smoking reference:rdataset-openintro-smoking’s home link. R package:openintro R Dataset:smoking

1243. Snowfall at Paradise, Mt. Rainier National Park

name:rdataset-openintro-snowfall reference:rdataset-openintro-snowfall’s home link. R package:openintro R Dataset:snowfall

1244. Social experiment

name:rdataset-openintro-socialexp reference:rdataset-openintro-socialexp’s home link. R package:openintro R Dataset:socialexp

1245. Energy Output From Two Solar Arrays in San Francisco

name:rdataset-openintro-solar reference:rdataset-openintro-solar’s home link. R package:openintro R Dataset:solar

1246. SOWC Child Mortality Data.

name:rdataset-openintro-sowc_child_mortality reference:rdataset-openintro-sowc_child_mortality’s home link. R package:openintro R Dataset:sowc_child_mortality

1247. SOWC Demographics Data.

name:rdataset-openintro-sowc_demographics reference:rdataset-openintro-sowc_demographics’s home link. R package:openintro R Dataset:sowc_demographics

1248. SOWC Maternal and Newborn Health Data.

name:rdataset-openintro-sowc_maternal_newborn reference:rdataset-openintro-sowc_maternal_newborn’s home link. R package:openintro R Dataset:sowc_maternal_newborn

1249. Financial information for 50 S&P 500 companies

name:rdataset-openintro-sp500 reference:rdataset-openintro-sp500’s home link. R package:openintro R Dataset:sp500

1250. Daily observations for the S&P 500

name:rdataset-openintro-sp500_1950_2018 reference:rdataset-openintro-sp500_1950_2018’s home link. R package:openintro R Dataset:sp500_1950_2018

1251. S&P 500 stock data

name:rdataset-openintro-sp500_seq reference:rdataset-openintro-sp500_seq’s home link. R package:openintro R Dataset:sp500_seq

1252. Speed, gender, and height of 1325 students

name:rdataset-openintro-speed_gender_height reference:rdataset-openintro-speed_gender_height’s home link. R package:openintro R Dataset:speed_gender_height

1253. SSD read and write speeds

name:rdataset-openintro-ssd_speed reference:rdataset-openintro-ssd_speed’s home link. R package:openintro R Dataset:ssd_speed

1254. Starbucks nutrition

name:rdataset-openintro-starbucks reference:rdataset-openintro-starbucks’s home link. R package:openintro R Dataset:starbucks

1255. Final exam scores for twenty students

name:rdataset-openintro-stats_scores reference:rdataset-openintro-stats_scores’s home link. R package:openintro R Dataset:stats_scores

1256. Embryonic stem cells to treat heart attack (in sheep)

name:rdataset-openintro-stem_cell reference:rdataset-openintro-stem_cell’s home link. R package:openintro R Dataset:stem_cell

1257. Stents for the treatment of stroke

name:rdataset-openintro-stent30 reference:rdataset-openintro-stent30’s home link. R package:openintro R Dataset:stent30

1258. Stents for the treatment of stroke

name:rdataset-openintro-stent365 reference:rdataset-openintro-stent365’s home link. R package:openintro R Dataset:stent365

1259. Monthly Returns for a few stocks

name:rdataset-openintro-stocks_18 reference:rdataset-openintro-stocks_18’s home link. R package:openintro R Dataset:stocks_18

1260. Community college housing (simulated data, 2015)

name:rdataset-openintro-student_housing reference:rdataset-openintro-student_housing’s home link. R package:openintro R Dataset:student_housing

1261. Sleep for 110 students (simulated)

name:rdataset-openintro-student_sleep reference:rdataset-openintro-student_sleep’s home link. R package:openintro R Dataset:student_sleep

1262. Treating heart attacks

name:rdataset-openintro-sulphinpyrazone reference:rdataset-openintro-sulphinpyrazone’s home link. R package:openintro R Dataset:sulphinpyrazone

1263. Supreme Court approval rating

name:rdataset-openintro-supreme_court reference:rdataset-openintro-supreme_court’s home link. R package:openintro R Dataset:supreme_court

1264. Teacher Salaries in St. Louis, Michigan

name:rdataset-openintro-teacher reference:rdataset-openintro-teacher’s home link. R package:openintro R Dataset:teacher

1265. Textbook data for UCLA Bookstore and Amazon

name:rdataset-openintro-textbooks reference:rdataset-openintro-textbooks’s home link. R package:openintro R Dataset:textbooks

1266. Thanksgiving spending, simulated based on Gallup poll.

name:rdataset-openintro-thanksgiving_spend reference:rdataset-openintro-thanksgiving_spend’s home link. R package:openintro R Dataset:thanksgiving_spend

1267. Tip data

name:rdataset-openintro-tips reference:rdataset-openintro-tips’s home link. R package:openintro R Dataset:tips

1268. Simulated polling data set

name:rdataset-openintro-toohey reference:rdataset-openintro-toohey’s home link. R package:openintro R Dataset:toohey

1269. Turkey tourism

name:rdataset-openintro-tourism reference:rdataset-openintro-tourism’s home link. R package:openintro R Dataset:tourism

1270. Simulated data set for ANOVA

name:rdataset-openintro-toy_anova reference:rdataset-openintro-toy_anova’s home link. R package:openintro R Dataset:toy_anova

1271. Transplant consultant success rate (fake data)

name:rdataset-openintro-transplant reference:rdataset-openintro-transplant’s home link. R package:openintro R Dataset:transplant

1272. UCLA courses in Fall 2018

name:rdataset-openintro-ucla_f18 reference:rdataset-openintro-ucla_f18’s home link. R package:openintro R Dataset:ucla_f18

1273. Sample of UCLA course textbooks for Fall 2018

name:rdataset-openintro-ucla_textbooks_f18 reference:rdataset-openintro-ucla_textbooks_f18’s home link. R package:openintro R Dataset:ucla_textbooks_f18

1274. United Kingdom Demographic Data

name:rdataset-openintro-ukdemo reference:rdataset-openintro-ukdemo’s home link. R package:openintro R Dataset:ukdemo

1275. Annual unemployment since 1890

name:rdataset-openintro-unempl reference:rdataset-openintro-unempl’s home link. R package:openintro R Dataset:unempl

1276. President’s party performance and unemployment rate

name:rdataset-openintro-unemploy_pres reference:rdataset-openintro-unemploy_pres’s home link. R package:openintro R Dataset:unemploy_pres

1277. Time Between Gondola Cars at Sterling Winery

name:rdataset-openintro-winery_cars reference:rdataset-openintro-winery_cars’s home link. R package:openintro R Dataset:winery_cars

1278. World Population Data.

name:rdataset-openintro-world_pop reference:rdataset-openintro-world_pop’s home link. R package:openintro R Dataset:world_pop

1279. Exxon Mobile stock data

name:rdataset-openintro-xom reference:rdataset-openintro-xom’s home link. R package:openintro R Dataset:xom

1280. Contagiousness of yawning

name:rdataset-openintro-yawn reference:rdataset-openintro-yawn’s home link. R package:openintro R Dataset:yawn

1281. Youth Risk Behavior Surveillance System (YRBSS)

name:rdataset-openintro-yrbss reference:rdataset-openintro-yrbss’s home link. R package:openintro R Dataset:yrbss

1282. Sample of Youth Risk Behavior Surveillance System (YRBSS)

name:rdataset-openintro-yrbss_samp reference:rdataset-openintro-yrbss_samp’s home link. R package:openintro R Dataset:yrbss_samp

1283. Size measurements for adult foraging penguins near Palmer Station, Antarctica

name:rdataset-palmerpenguins-penguins reference:rdataset-palmerpenguins-penguins’s home link. R package:palmerpenguins R Dataset:penguins

1284. Cigarette Consumption

name:rdataset-plm-cigar reference:rdataset-plm-cigar’s home link. R package:plm R Dataset:cigar

1285. Crime in North Carolina

name:rdataset-plm-crime reference:rdataset-plm-crime’s home link. R package:plm R Dataset:crime

1286. Employment and Wages in the United Kingdom

name:rdataset-plm-empluk reference:rdataset-plm-empluk’s home link. R package:plm R Dataset:empluk

1287. Gasoline Consumption

name:rdataset-plm-gasoline reference:rdataset-plm-gasoline’s home link. R package:plm R Dataset:gasoline

1288. Grunfeld’s Investment Data

name:rdataset-plm-grunfeld reference:rdataset-plm-grunfeld’s home link. R package:plm R Dataset:grunfeld

1289. Hedonic Prices of Census Tracts in the Boston Area

name:rdataset-plm-hedonic reference:rdataset-plm-hedonic’s home link. R package:plm R Dataset:hedonic

1290. Wages and Hours Worked

name:rdataset-plm-laborsupply reference:rdataset-plm-laborsupply’s home link. R package:plm R Dataset:laborsupply

1291. Wages and Education of Young Males

name:rdataset-plm-males reference:rdataset-plm-males’s home link. R package:plm R Dataset:males

1292. Purchasing Power Parity and other parity relationships

name:rdataset-plm-parity reference:rdataset-plm-parity’s home link. R package:plm R Dataset:parity

1293. US States Production

name:rdataset-plm-produc reference:rdataset-plm-produc’s home link. R package:plm R Dataset:produc

1294. Production of Rice in Indonesia

name:rdataset-plm-ricefarms reference:rdataset-plm-ricefarms’s home link. R package:plm R Dataset:ricefarms

1295. Employment and Wages in Spain

name:rdataset-plm-snmesp reference:rdataset-plm-snmesp’s home link. R package:plm R Dataset:snmesp

1296. The Penn World Table, v. 5

name:rdataset-plm-sumhes reference:rdataset-plm-sumhes’s home link. R package:plm R Dataset:sumhes

1297. Panel Data of Individual Wages

name:rdataset-plm-wages reference:rdataset-plm-wages’s home link. R package:plm R Dataset:wages

1298. Yearly batting records for all major league baseball players

name:rdataset-plyr-baseball reference:rdataset-plyr-baseball’s home link. R package:plyr R Dataset:baseball

1299. Monthly ozone measurements over Central America.

name:rdataset-plyr-ozone reference:rdataset-plyr-ozone’s home link. R package:plyr R Dataset:ozone

1300. Absentee and Machine Ballots in Pennsylvania State Senate Races

name:rdataset-pscl-absentee reference:rdataset-pscl-absentee’s home link. R package:pscl R Dataset:absentee

1301. Applications to a Political Science PhD Program

name:rdataset-pscl-admit reference:rdataset-pscl-admit’s home link. R package:pscl R Dataset:admit

1302. Political opinion polls in Australia, 2004-07

name:rdataset-pscl-australianelectionpolling reference:rdataset-pscl-australianelectionpolling’s home link. R package:pscl R Dataset:australianelectionpolling

1303. elections to Australian House of Representatives, 1949-2016

name:rdataset-pscl-australianelections reference:rdataset-pscl-australianelections’s home link. R package:pscl R Dataset:australianelections

1304. article production by graduate students in biochemistry Ph.D. programs

name:rdataset-pscl-biochemists reference:rdataset-pscl-biochemists’s home link. R package:pscl R Dataset:biochemists

1305. California Congressional Districts in 2006

name:rdataset-pscl-ca2006 reference:rdataset-pscl-ca2006’s home link. R package:pscl R Dataset:ca2006

1306. Batting Averages for 18 major league baseball players, 1970

name:rdataset-pscl-efronmorris reference:rdataset-pscl-efronmorris’s home link. R package:pscl R Dataset:efronmorris

1307. U.S. Senate vote on the use of force against Iraq, 2002.

name:rdataset-pscl-iraqvote reference:rdataset-pscl-iraqvote’s home link. R package:pscl R Dataset:iraqvote

1308. political parties appearing in the U.S. Congress

name:rdataset-pscl-partycodes reference:rdataset-pscl-partycodes’s home link. R package:pscl R Dataset:partycodes

1309. Interviewer ratings of respondent levels of political information

name:rdataset-pscl-politicalinformation reference:rdataset-pscl-politicalinformation’s home link. R package:pscl R Dataset:politicalinformation

1310. elections for U.S. President, 1932-2016, by state

name:rdataset-pscl-presidentialelections reference:rdataset-pscl-presidentialelections’s home link. R package:pscl R Dataset:presidentialelections

1311. Prussian army horse kick data

name:rdataset-pscl-prussian reference:rdataset-pscl-prussian’s home link. R package:pscl R Dataset:prussian

1312. Voter turnout experiment, using Rock The Vote ads

name:rdataset-pscl-rockthevote reference:rdataset-pscl-rockthevote’s home link. R package:pscl R Dataset:rockthevote

1313. information about the American states needed for U.S. Congress

name:rdataset-pscl-state.info reference:rdataset-pscl-state.info’s home link. R package:pscl R Dataset:state.info

1314. 1992 United Kingdom electoral returns

name:rdataset-pscl-ukhouseofcommons reference:rdataset-pscl-ukhouseofcommons’s home link. R package:pscl R Dataset:ukhouseofcommons

1315. cross national rates of trade union density

name:rdataset-pscl-uniondensity reference:rdataset-pscl-uniondensity’s home link. R package:pscl R Dataset:uniondensity

1316. Reports of voting in the 1992 U.S. Presidential election.

name:rdataset-pscl-vote92 reference:rdataset-pscl-vote92’s home link. R package:pscl R Dataset:vote92

1317. Seven data sets showing a bifactor solution.

name:rdataset-psych-bechtoldt reference:rdataset-psych-bechtoldt’s home link. R package:psych R Dataset:bechtoldt

1318. Seven data sets showing a bifactor solution.

name:rdataset-psych-bechtoldt.1 reference:rdataset-psych-bechtoldt.1’s home link. R package:psych R Dataset:bechtoldt.1

1319. Seven data sets showing a bifactor solution.

name:rdataset-psych-bechtoldt.2 reference:rdataset-psych-bechtoldt.2’s home link. R package:psych R Dataset:bechtoldt.2

1320. 25 Personality items representing 5 factors

name:rdataset-psych-bfi reference:rdataset-psych-bfi’s home link. R package:psych R Dataset:bfi

1321. 12 cognitive variables from Cattell (1963)

name:rdataset-psych-cattell reference:rdataset-psych-cattell’s home link. R package:psych R Dataset:cattell

1322. 8 cognitive variables used by Dwyer for an example.

name:rdataset-psych-dwyer reference:rdataset-psych-dwyer’s home link. R package:psych R Dataset:dwyer

1323. Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.

name:rdataset-psych-gleser reference:rdataset-psych-gleser’s home link. R package:psych R Dataset:gleser

1324. Example data set from Gorsuch (1997) for an example factor extension.

name:rdataset-psych-gorsuch reference:rdataset-psych-gorsuch’s home link. R package:psych R Dataset:gorsuch

1325. Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt

name:rdataset-psych-harman.5 reference:rdataset-psych-harman.5’s home link. R package:psych R Dataset:harman.5

1326. Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt

name:rdataset-psych-harman.8 reference:rdataset-psych-harman.8’s home link. R package:psych R Dataset:harman.8

1327. Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt

name:rdataset-psych-harman.political reference:rdataset-psych-harman.political’s home link. R package:psych R Dataset:harman.political

1328. Seven data sets showing a bifactor solution.

name:rdataset-psych-holzinger reference:rdataset-psych-holzinger’s home link. R package:psych R Dataset:holzinger

1329. Seven data sets showing a bifactor solution.

name:rdataset-psych-holzinger.9 reference:rdataset-psych-holzinger.9’s home link. R package:psych R Dataset:holzinger.9

1330. Seven data sets showing a bifactor solution.

name:rdataset-psych-reise reference:rdataset-psych-reise’s home link. R package:psych R Dataset:reise

1331. 3 Measures of ability: SATV, SATQ, ACT

name:rdataset-psych-sat.act reference:rdataset-psych-sat.act’s home link. R package:psych R Dataset:sat.act

1332. 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation

name:rdataset-psych-schmid reference:rdataset-psych-schmid’s home link. R package:psych R Dataset:schmid

1333. Data set testing causal direction in presumed media influence

name:rdataset-psych-tal.or reference:rdataset-psych-tal.or’s home link. R package:psych R Dataset:tal.or

1334. Seven data sets showing a bifactor solution.

name:rdataset-psych-thurstone reference:rdataset-psych-thurstone’s home link. R package:psych R Dataset:thurstone

1335. Seven data sets showing a bifactor solution.

name:rdataset-psych-thurstone.33 reference:rdataset-psych-thurstone.33’s home link. R package:psych R Dataset:thurstone.33

1336. Seven data sets showing a bifactor solution.

name:rdataset-psych-thurstone.9 reference:rdataset-psych-thurstone.9’s home link. R package:psych R Dataset:thurstone.9

1337. 9 Cognitive variables discussed by Tucker and Lewis (1973)

name:rdataset-psych-tucker reference:rdataset-psych-tucker’s home link. R package:psych R Dataset:tucker

1338. An example of the distinction between within group and between group correlations

name:rdataset-psych-withinbetween reference:rdataset-psych-withinbetween’s home link. R package:psych R Dataset:withinbetween

1339. Barro Data

name:rdataset-quantreg-barro reference:rdataset-quantreg-barro’s home link. R package:quantreg R Dataset:barro

1340. Boscovich Data

name:rdataset-quantreg-bosco reference:rdataset-quantreg-bosco’s home link. R package:quantreg R Dataset:bosco

1341. Cobar Ore data

name:rdataset-quantreg-cobarore reference:rdataset-quantreg-cobarore’s home link. R package:quantreg R Dataset:cobarore

1342. Engel Data

name:rdataset-quantreg-engel reference:rdataset-quantreg-engel’s home link. R package:quantreg R Dataset:engel

1343. Time Series of US Gasoline Prices

name:rdataset-quantreg-gasprice reference:rdataset-quantreg-gasprice’s home link. R package:quantreg R Dataset:gasprice

1344. Garland(1983) Data on Running Speed of Mammals

name:rdataset-quantreg-mammals reference:rdataset-quantreg-mammals’s home link. R package:quantreg R Dataset:mammals

1345. UIS Drug Treatment study data

name:rdataset-quantreg-uis reference:rdataset-quantreg-uis’s home link. R package:quantreg R Dataset:uis

1346. Complete survey data.

name:rdataset-ratdat-complete reference:rdataset-ratdat-complete’s home link. R package:ratdat R Dataset:complete

1347. Complete survey data from 1977 to 1989.

name:rdataset-ratdat-complete_old reference:rdataset-ratdat-complete_old’s home link. R package:ratdat R Dataset:complete_old

1348. Plots data.

name:rdataset-ratdat-plots reference:rdataset-ratdat-plots’s home link. R package:ratdat R Dataset:plots

1349. Species data.

name:rdataset-ratdat-species reference:rdataset-ratdat-species’s home link. R package:ratdat R Dataset:species

1350. Survey data.

name:rdataset-ratdat-surveys reference:rdataset-ratdat-surveys’s home link. R package:ratdat R Dataset:surveys

1351. Sensory data from a french fries experiment.

name:rdataset-reshape2-french_fries reference:rdataset-reshape2-french_fries’s home link. R package:reshape2 R Dataset:french_fries

1352. Demo data describing the Smiths.

name:rdataset-reshape2-smiths reference:rdataset-reshape2-smiths’s home link. R package:reshape2 R Dataset:smiths

1353. Tipping data

name:rdataset-reshape2-tips reference:rdataset-reshape2-tips’s home link. R package:reshape2 R Dataset:tips

1354. Aircraft Data

name:rdataset-robustbase-aircraft reference:rdataset-robustbase-aircraft’s home link. R package:robustbase R Dataset:aircraft

1355. Air Quality Data

name:rdataset-robustbase-airmay reference:rdataset-robustbase-airmay’s home link. R package:robustbase R Dataset:airmay

1356. Alcohol Solubility in Water Data

name:rdataset-robustbase-alcohol reference:rdataset-robustbase-alcohol’s home link. R package:robustbase R Dataset:alcohol

1357. Daily Means of NOx (mono-nitrogen oxides) in air

name:rdataset-robustbase-ambientnoxch reference:rdataset-robustbase-ambientnoxch’s home link. R package:robustbase R Dataset:ambientnoxch

1358. Brain and Body Weights for 65 Species of Land Animals

name:rdataset-robustbase-animals2 reference:rdataset-robustbase-animals2’s home link. R package:robustbase R Dataset:animals2

1359. Biomass Tillage Data

name:rdataset-robustbase-biomasstill reference:rdataset-robustbase-biomasstill’s home link. R package:robustbase R Dataset:biomasstill

1360. Campbell Bushfire Data

name:rdataset-robustbase-bushfire reference:rdataset-robustbase-bushfire’s home link. R package:robustbase R Dataset:bushfire

1361. Insect Damages on Carrots

name:rdataset-robustbase-carrots reference:rdataset-robustbase-carrots’s home link. R package:robustbase R Dataset:carrots

1362. Cloud point of a Liquid

name:rdataset-robustbase-cloud reference:rdataset-robustbase-cloud’s home link. R package:robustbase R Dataset:cloud

1363. Coleman Data Set

name:rdataset-robustbase-coleman reference:rdataset-robustbase-coleman’s home link. R package:robustbase R Dataset:coleman

1364. Condroz Data

name:rdataset-robustbase-condroz reference:rdataset-robustbase-condroz’s home link. R package:robustbase R Dataset:condroz

1365. Crohn’s Disease Adverse Events Data

name:rdataset-robustbase-crohnd reference:rdataset-robustbase-crohnd’s home link. R package:robustbase R Dataset:crohnd

1366. Cushny and Peebles Prolongation of Sleep Data

name:rdataset-robustbase-cushny reference:rdataset-robustbase-cushny’s home link. R package:robustbase R Dataset:cushny

1367. Delivery Time Data

name:rdataset-robustbase-delivery reference:rdataset-robustbase-delivery’s home link. R package:robustbase R Dataset:delivery

1368. Education Expenditure Data

name:rdataset-robustbase-education reference:rdataset-robustbase-education’s home link. R package:robustbase R Dataset:education

1369. Epilepsy Attacks Data Set

name:rdataset-robustbase-epilepsy reference:rdataset-robustbase-epilepsy’s home link. R package:robustbase R Dataset:epilepsy

1370. Example Data of Antille and May - for Simple Regression

name:rdataset-robustbase-exam reference:rdataset-robustbase-exam’s home link. R package:robustbase R Dataset:exam

1371. Food Stamp Program Participation

name:rdataset-robustbase-foodstamp reference:rdataset-robustbase-foodstamp’s home link. R package:robustbase R Dataset:foodstamp

1372. Hawkins, Bradu, Kass’s Artificial Data

name:rdataset-robustbase-hbk reference:rdataset-robustbase-hbk’s home link. R package:robustbase R Dataset:hbk

1373. Heart Catherization Data

name:rdataset-robustbase-heart reference:rdataset-robustbase-heart’s home link. R package:robustbase R Dataset:heart

1374. Waterflow Measurements of Kootenay River in Libby and Newgate

name:rdataset-robustbase-kootenay reference:rdataset-robustbase-kootenay’s home link. R package:robustbase R Dataset:kootenay

1375. Lactic Acid Concentration Measurement Data

name:rdataset-robustbase-lactic reference:rdataset-robustbase-lactic’s home link. R package:robustbase R Dataset:lactic

1376. Length of Stay Data

name:rdataset-robustbase-los reference:rdataset-robustbase-los’s home link. R package:robustbase R Dataset:los

1377. Daudin’s Milk Composition Data

name:rdataset-robustbase-milk reference:rdataset-robustbase-milk’s home link. R package:robustbase R Dataset:milk

1378. NOx Air Pollution Data

name:rdataset-robustbase-noxemissions reference:rdataset-robustbase-noxemissions’s home link. R package:robustbase R Dataset:noxemissions

1379. Pension Funds Data

name:rdataset-robustbase-pension reference:rdataset-robustbase-pension’s home link. R package:robustbase R Dataset:pension

1380. Phosphorus Content Data

name:rdataset-robustbase-phosphor reference:rdataset-robustbase-phosphor’s home link. R package:robustbase R Dataset:phosphor

1381. Pilot-Plant Data

name:rdataset-robustbase-pilot reference:rdataset-robustbase-pilot’s home link. R package:robustbase R Dataset:pilot

1382. Possum Diversity Data

name:rdataset-robustbase-possumdiv reference:rdataset-robustbase-possumdiv’s home link. R package:robustbase R Dataset:possumdiv

1383. Pulp Fiber and Paper Data

name:rdataset-robustbase-pulpfiber reference:rdataset-robustbase-pulpfiber’s home link. R package:robustbase R Dataset:pulpfiber

1384. Satellite Radar Image Data from near Munich

name:rdataset-robustbase-radarimage reference:rdataset-robustbase-radarimage’s home link. R package:robustbase R Dataset:radarimage

1385. Salinity Data

name:rdataset-robustbase-salinity reference:rdataset-robustbase-salinity’s home link. R package:robustbase R Dataset:salinity

1386. Siegel’s Exact Fit Example Data

name:rdataset-robustbase-siegelsex reference:rdataset-robustbase-siegelsex’s home link. R package:robustbase R Dataset:siegelsex

1387. Hertzsprung-Russell Diagram Data of Star Cluster CYG OB1

name:rdataset-robustbase-starscyg reference:rdataset-robustbase-starscyg’s home link. R package:robustbase R Dataset:starscyg

1388. Steam Usage Data (Excerpt)

name:rdataset-robustbase-steamuse reference:rdataset-robustbase-steamuse’s home link. R package:robustbase R Dataset:steamuse

1389. Number of International Calls from Belgium

name:rdataset-robustbase-telef reference:rdataset-robustbase-telef’s home link. R package:robustbase R Dataset:telef

1390. Toxicity of Carboxylic Acids Data

name:rdataset-robustbase-toxicity reference:rdataset-robustbase-toxicity’s home link. R package:robustbase R Dataset:toxicity

1391. Vaso Constriction Skin Data Set

name:rdataset-robustbase-vaso reference:rdataset-robustbase-vaso’s home link. R package:robustbase R Dataset:vaso

1392. Wagner’s Hannover Employment Growth Data

name:rdataset-robustbase-wagnergrowth reference:rdataset-robustbase-wagnergrowth’s home link. R package:robustbase R Dataset:wagnergrowth

1393. Modified Data on Wood Specific Gravity

name:rdataset-robustbase-wood reference:rdataset-robustbase-wood’s home link. R package:robustbase R Dataset:wood

1394. Extreme Data examples

name:rdataset-robustbase-x30o50 reference:rdataset-robustbase-x30o50’s home link. R package:robustbase R Dataset:x30o50

1395. Automobile Data from ‘Consumer Reports’ 1990

name:rdataset-rpart-car.test.frame reference:rdataset-rpart-car.test.frame’s home link. R package:rpart R Dataset:car.test.frame

1396. Automobile Data from ‘Consumer Reports’ 1990

name:rdataset-rpart-car90 reference:rdataset-rpart-car90’s home link. R package:rpart R Dataset:car90

1397. Automobile Data from ‘Consumer Reports’ 1990

name:rdataset-rpart-cu.summary reference:rdataset-rpart-cu.summary’s home link. R package:rpart R Dataset:cu.summary

1398. Data on Children who have had Corrective Spinal Surgery

name:rdataset-rpart-kyphosis reference:rdataset-rpart-kyphosis’s home link. R package:rpart R Dataset:kyphosis

1399. Soldering of Components on Printed-Circuit Boards

name:rdataset-rpart-solder reference:rdataset-rpart-solder’s home link. R package:rpart R Dataset:solder

1400. Stage C Prostate Cancer

name:rdataset-rpart-stagec reference:rdataset-rpart-stagec’s home link. R package:rpart R Dataset:stagec

1401. Innovation and Institutional Ownership

name:rdataset-sandwich-instinnovation reference:rdataset-sandwich-instinnovation’s home link. R package:sandwich R Dataset:instinnovation

1402. US Investment Data

name:rdataset-sandwich-investment reference:rdataset-sandwich-investment’s home link. R package:sandwich R Dataset:investment

1403. Petersen’s Simulated Data for Assessing Clustered Standard Errors

name:rdataset-sandwich-petersencl reference:rdataset-sandwich-petersencl’s home link. R package:sandwich R Dataset:petersencl

1404. US Expenditures for Public Schools

name:rdataset-sandwich-publicschools reference:rdataset-sandwich-publicschools’s home link. R package:sandwich R Dataset:publicschools

1405. Bollen’s Data on Industrialization and Political Democracy

name:rdataset-sem-bollen reference:rdataset-sem-bollen’s home link. R package:sem R Dataset:bollen

1406. Variables from the 1997 Canadian National Election Study

name:rdataset-sem-cnes reference:rdataset-sem-cnes’s home link. R package:sem R Dataset:cnes

1407. Holizinger and Swineford’s Data

name:rdataset-sem-hs.data reference:rdataset-sem-hs.data’s home link. R package:sem R Dataset:hs.data

1408. Klein’s Data on the U. S. Economy

name:rdataset-sem-klein reference:rdataset-sem-klein’s home link. R package:sem R Dataset:klein

1409. Partly Artificial Data on the U. S. Economy

name:rdataset-sem-kmenta reference:rdataset-sem-kmenta’s home link. R package:sem R Dataset:kmenta

1410. Six Mental Tests

name:rdataset-sem-tests reference:rdataset-sem-tests’s home link. R package:sem R Dataset:tests

1411. Prices of Used Honda Accords (in 2017)

name:rdataset-stat2data-accordprice reference:rdataset-stat2data-accordprice’s home link. R package:stat2data R Dataset:accordprice

1412. Congressional Votes on American Health Care Act (in 2017)

name:rdataset-stat2data-ahcavote2017 reference:rdataset-stat2data-ahcavote2017’s home link. R package:stat2data R Dataset:ahcavote2017

1413. Ontime Records for Two Airlines at Two Airports

name:rdataset-stat2data-airlines reference:rdataset-stat2data-airlines’s home link. R package:stat2data R Dataset:airlines

1414. Alfalfa Growth

name:rdataset-stat2data-alfalfa reference:rdataset-stat2data-alfalfa’s home link. R package:stat2data R Dataset:alfalfa

1415. US Senate Votes on Samuel Alito for the Supreme Court

name:rdataset-stat2data-alitoconfirmation reference:rdataset-stat2data-alitoconfirmation’s home link. R package:stat2data R Dataset:alitoconfirmation

1416. Amyloid-beta and Cognitive Impairment

name:rdataset-stat2data-amyloid reference:rdataset-stat2data-amyloid’s home link. R package:stat2data R Dataset:amyloid

1417. Daily Price and Volume of Apple Stock

name:rdataset-stat2data-applestock reference:rdataset-stat2data-applestock’s home link. R package:stat2data R Dataset:applestock

1418. Scores in an Archery Class

name:rdataset-stat2data-archerydata reference:rdataset-stat2data-archerydata’s home link. R package:stat2data R Dataset:archerydata

1419. Athletic Participation, Race, and Graduation

name:rdataset-stat2data-athletegrad reference:rdataset-stat2data-athletegrad’s home link. R package:stat2data R Dataset:athletegrad

1420. Reaction Times to Audio and Visual Stimuli

name:rdataset-stat2data-audiovisual reference:rdataset-stat2data-audiovisual’s home link. R package:stat2data R Dataset:audiovisual

1421. Noise Levels of Filters to Reduce Automobile Pollution

name:rdataset-stat2data-autopollution reference:rdataset-stat2data-autopollution’s home link. R package:stat2data R Dataset:autopollution

1422. Weights of College Student Backpacks

name:rdataset-stat2data-backpack reference:rdataset-stat2data-backpack’s home link. R package:stat2data R Dataset:backpack

1423. Baseball Game Times of One Day in 2008

name:rdataset-stat2data-baseballtimes reference:rdataset-stat2data-baseballtimes’s home link. R package:stat2data R Dataset:baseballtimes

1424. Baseball Game Times of One Day in 2017

name:rdataset-stat2data-baseballtimes2017 reference:rdataset-stat2data-baseballtimes2017’s home link. R package:stat2data R Dataset:baseballtimes2017

1425. Do Bee Stings Depend on Previous Stings?

name:rdataset-stat2data-beestings reference:rdataset-stat2data-beestings’s home link. R package:stat2data R Dataset:beestings

1426. Effect of a Hormone on Bird Calcium Levels

name:rdataset-stat2data-birdcalcium reference:rdataset-stat2data-birdcalcium’s home link. R package:stat2data R Dataset:birdcalcium

1427. Nest Characteristics for Different Bird Species

name:rdataset-stat2data-birdnest reference:rdataset-stat2data-birdnest’s home link. R package:stat2data R Dataset:birdnest

1428. Blood Pressure, Weight, and Smoking Status

name:rdataset-stat2data-blood1 reference:rdataset-stat2data-blood1’s home link. R package:stat2data R Dataset:blood1

1429. Blue Jay Measurements

name:rdataset-stat2data-bluejays reference:rdataset-stat2data-bluejays’s home link. R package:stat2data R Dataset:bluejays

1430. Brain pH Measurements

name:rdataset-stat2data-brainph reference:rdataset-stat2data-brainph’s home link. R package:stat2data R Dataset:brainph

1431. Drew Brees Passing Statistics (2016)

name:rdataset-stat2data-breespass reference:rdataset-stat2data-breespass’s home link. R package:stat2data R Dataset:breespass

1432. Attitudes Towards British Trade Unions

name:rdataset-stat2data-britishunions reference:rdataset-stat2data-britishunions’s home link. R package:stat2data R Dataset:britishunions

1433. Butterfly (Boloria chariclea) Measurements

name:rdataset-stat2data-butterfliesbc reference:rdataset-stat2data-butterfliesbc’s home link. R package:stat2data R Dataset:butterfliesbc

1434. US Senate Votes on Corporate Average Fuel Economy Bill

name:rdataset-stat2data-cafe reference:rdataset-stat2data-cafe’s home link. R package:stat2data R Dataset:cafe

1435. Do Calcium Supplements Lower Blood Pressure?

name:rdataset-stat2data-calciumbp reference:rdataset-stat2data-calciumbp’s home link. R package:stat2data R Dataset:calciumbp

1436. Canadian Drugs Senate Vote

name:rdataset-stat2data-canadiandrugs reference:rdataset-stat2data-canadiandrugs’s home link. R package:stat2data R Dataset:canadiandrugs

1437. Survival Times for Different Cancers

name:rdataset-stat2data-cancersurvival reference:rdataset-stat2data-cancersurvival’s home link. R package:stat2data R Dataset:cancersurvival

1438. Measurements of Manduca Sexta Caterpillars

name:rdataset-stat2data-caterpillars reference:rdataset-stat2data-caterpillars’s home link. R package:stat2data R Dataset:caterpillars

1439. Cleveland Cavalier’s Shooting (2016-2017)

name:rdataset-stat2data-cavsshooting reference:rdataset-stat2data-cavsshooting’s home link. R package:stat2data R Dataset:cavsshooting

1440. Nutrition Content of Breakfast Cereals

name:rdataset-stat2data-cereal reference:rdataset-stat2data-cereal’s home link. R package:stat2data R Dataset:cereal

1441. THC for Antinausea Treatment in Chemotherapy

name:rdataset-stat2data-chemothc reference:rdataset-stat2data-chemothc’s home link. R package:stat2data R Dataset:chemothc

1442. Age at First Speaking

name:rdataset-stat2data-childspeaks reference:rdataset-stat2data-childspeaks’s home link. R package:stat2data R Dataset:childspeaks

1443. Clinton/Sanders Primary Results (2016)

name:rdataset-stat2data-clintonsanders reference:rdataset-stat2data-clintonsanders’s home link. R package:stat2data R Dataset:clintonsanders

1444. Sales for a Clothing Retailer

name:rdataset-stat2data-clothing reference:rdataset-stat2data-clothing’s home link. R package:stat2data R Dataset:clothing

1445. Cloud Seeding Experiment (Winter Only)

name:rdataset-stat2data-cloudseeding reference:rdataset-stat2data-cloudseeding’s home link. R package:stat2data R Dataset:cloudseeding

1446. Cloud Seeding Experiment (Four Seasons)

name:rdataset-stat2data-cloudseeding2 reference:rdataset-stat2data-cloudseeding2’s home link. R package:stat2data R Dataset:cloudseeding2

1447. Daily CO2 Measurements in Germany

name:rdataset-stat2data-co2 reference:rdataset-stat2data-co2’s home link. R package:stat2data R Dataset:co2

1448. Daily CO2 Measurements in Germany

name:rdataset-stat2data-co2germany reference:rdataset-stat2data-co2germany’s home link. R package:stat2data R Dataset:co2germany

1449. CO2 Readings in Hawaii

name:rdataset-stat2data-co2hawaii reference:rdataset-stat2data-co2hawaii’s home link. R package:stat2data R Dataset:co2hawaii

1450. CO2 Readings at the South Pole

name:rdataset-stat2data-co2southpole reference:rdataset-stat2data-co2southpole’s home link. R package:stat2data R Dataset:co2southpole

1451. Drug Interaction with Contraceptives

name:rdataset-stat2data-contraceptives reference:rdataset-stat2data-contraceptives’s home link. R package:stat2data R Dataset:contraceptives

1452. County Health Resources

name:rdataset-stat2data-countyhealth reference:rdataset-stat2data-countyhealth’s home link. R package:stat2data R Dataset:countyhealth

1453. Crab Oxygen Intake

name:rdataset-stat2data-crabship reference:rdataset-stat2data-crabship’s home link. R package:stat2data R Dataset:crabship

1454. Effects of Cracker Fiber on Digested Calories

name:rdataset-stat2data-crackerfiber reference:rdataset-stat2data-crackerfiber’s home link. R package:stat2data R Dataset:crackerfiber

1455. Overdrawn Checking Account?

name:rdataset-stat2data-creditrisk reference:rdataset-stat2data-creditrisk’s home link. R package:stat2data R Dataset:creditrisk

1456. Measurements of Cuckoo Eggs

name:rdataset-stat2data-cuckoo reference:rdataset-stat2data-cuckoo’s home link. R package:stat2data R Dataset:cuckoo

1457. First Day Survey of Statistics Students

name:rdataset-stat2data-day1survey reference:rdataset-stat2data-day1survey’s home link. R package:stat2data R Dataset:day1survey

1458. Lactic Acid Turnover in Dogs

name:rdataset-stat2data-diabeticdogs reference:rdataset-stat2data-diabeticdogs’s home link. R package:stat2data R Dataset:diabeticdogs

1459. Characteristics of a Sample of Diamonds

name:rdataset-stat2data-diamonds reference:rdataset-stat2data-diamonds’s home link. R package:stat2data R Dataset:diamonds

1460. Characteristics of a Subset of the Diamond Sample

name:rdataset-stat2data-diamonds2 reference:rdataset-stat2data-diamonds2’s home link. R package:stat2data R Dataset:diamonds2

1461. Iridium Levels in Rock Layers to Investigate Dinosaur Extinction

name:rdataset-stat2data-dinosaurs reference:rdataset-stat2data-dinosaurs’s home link. R package:stat2data R Dataset:dinosaurs

1462. 2008 U.S. Presidential Election

name:rdataset-stat2data-election08 reference:rdataset-stat2data-election08’s home link. R package:stat2data R Dataset:election08

1463. 2016 U.S. Presidential Election

name:rdataset-stat2data-election16 reference:rdataset-stat2data-election16’s home link. R package:stat2data R Dataset:election16

1464. Measurements of Male African Elephants

name:rdataset-stat2data-elephantsfb reference:rdataset-stat2data-elephantsfb’s home link. R package:stat2data R Dataset:elephantsfb

1465. Measurements of African Elephants

name:rdataset-stat2data-elephantsmf reference:rdataset-stat2data-elephantsmf’s home link. R package:stat2data R Dataset:elephantsmf

1466. Effects of Oxygen on Sugar Metabolism

name:rdataset-stat2data-ethanol reference:rdataset-stat2data-ethanol’s home link. R package:stat2data R Dataset:ethanol

1467. Pupil Dilation and Sexual Orientation

name:rdataset-stat2data-eyes reference:rdataset-stat2data-eyes’s home link. R package:stat2data R Dataset:eyes

1468. Facial Attractiveness of Men

name:rdataset-stat2data-faces reference:rdataset-stat2data-faces’s home link. R package:stat2data R Dataset:faces

1469. Faithfulness from a Photo?

name:rdataset-stat2data-faithfulfaces reference:rdataset-stat2data-faithfulfaces’s home link. R package:stat2data R Dataset:faithfulfaces

1470. Selection Times in a Fantasy Baseball Draft

name:rdataset-stat2data-fantasybaseball reference:rdataset-stat2data-fantasybaseball’s home link. R package:stat2data R Dataset:fantasybaseball

1471. Diet and Weight of Rats

name:rdataset-stat2data-fatrats reference:rdataset-stat2data-fatrats’s home link. R package:stat2data R Dataset:fatrats

1472. Fertility Data for Women Having Trouble Getting Pregnant

name:rdataset-stat2data-fertility reference:rdataset-stat2data-fertility’s home link. R package:stat2data R Dataset:fertility

1473. Results of NFL Field Goal Attempts

name:rdataset-stat2data-fgbydistance reference:rdataset-stat2data-fgbydistance’s home link. R package:stat2data R Dataset:fgbydistance

1474. Film Data from Leonard Maltin’s Guide

name:rdataset-stat2data-film reference:rdataset-stat2data-film’s home link. R package:stat2data R Dataset:film

1475. NCAA Final Four by Seed and Tom Izzo (through 2010)

name:rdataset-stat2data-finalfourizzo reference:rdataset-stat2data-finalfourizzo’s home link. R package:stat2data R Dataset:finalfourizzo

1476. NCAA Final Four by Seed and Tom Izzo (through 2017)

name:rdataset-stat2data-finalfourizzo17 reference:rdataset-stat2data-finalfourizzo17’s home link. R package:stat2data R Dataset:finalfourizzo17

1477. NCAA Final Four by Seed (Long Version through 2010)

name:rdataset-stat2data-finalfourlong reference:rdataset-stat2data-finalfourlong’s home link. R package:stat2data R Dataset:finalfourlong

1478. NCAA Final Four by Seed (Long Version through 2017)

name:rdataset-stat2data-finalfourlong17 reference:rdataset-stat2data-finalfourlong17’s home link. R package:stat2data R Dataset:finalfourlong17

1479. CAA Final Four by Seed (Short Version through 2010)

name:rdataset-stat2data-finalfourshort reference:rdataset-stat2data-finalfourshort’s home link. R package:stat2data R Dataset:finalfourshort

1480. NCAA Final Four by Seed (Short Version through 2017)

name:rdataset-stat2data-finalfourshort17 reference:rdataset-stat2data-finalfourshort17’s home link. R package:stat2data R Dataset:finalfourshort17

1481. Finger Tap Rates

name:rdataset-stat2data-fingers reference:rdataset-stat2data-fingers’s home link. R package:stat2data R Dataset:fingers

1482. First Year GPA for College Students

name:rdataset-stat2data-firstyeargpa reference:rdataset-stat2data-firstyeargpa’s home link. R package:stat2data R Dataset:firstyeargpa

1483. Fertility of Fish Eggs

name:rdataset-stat2data-fisheggs reference:rdataset-stat2data-fisheggs’s home link. R package:stat2data R Dataset:fisheggs

1484. Body Measurements of Mammal Species

name:rdataset-stat2data-fitch reference:rdataset-stat2data-fitch’s home link. R package:stat2data R Dataset:fitch

1485. Response of Migratory Geese to Helicopter Overflights

name:rdataset-stat2data-flightresponse reference:rdataset-stat2data-flightresponse’s home link. R package:stat2data R Dataset:flightresponse

1486. Florida Death Penalty Cases

name:rdataset-stat2data-floridadp reference:rdataset-stat2data-floridadp’s home link. R package:stat2data R Dataset:floridadp

1487. Measuring Calcium Binding to Proteins

name:rdataset-stat2data-fluorescence reference:rdataset-stat2data-fluorescence’s home link. R package:stat2data R Dataset:fluorescence

1488. Finger Tap Rates

name:rdataset-stat2data-franticfingers reference:rdataset-stat2data-franticfingers’s home link. R package:stat2data R Dataset:franticfingers

1489. Fruit Fly Sexual Activity and Longevity

name:rdataset-stat2data-fruitflies reference:rdataset-stat2data-fruitflies’s home link. R package:stat2data R Dataset:fruitflies

1490. Fruit Fly Sexual Activity and Male Competition

name:rdataset-stat2data-fruitflies2 reference:rdataset-stat2data-fruitflies2’s home link. R package:stat2data R Dataset:fruitflies2

1491. Funnel Drop Times

name:rdataset-stat2data-funneldrop reference:rdataset-stat2data-funneldrop’s home link. R package:stat2data R Dataset:funneldrop

1492. Female Glow-worms

name:rdataset-stat2data-glowworms reference:rdataset-stat2data-glowworms’s home link. R package:stat2data R Dataset:glowworms

1493. Goldenrod Galls

name:rdataset-stat2data-goldenrod reference:rdataset-stat2data-goldenrod’s home link. R package:stat2data R Dataset:goldenrod

1494. House Sales in Grinnell, Iowa

name:rdataset-stat2data-grinnellhouses reference:rdataset-stat2data-grinnellhouses’s home link. R package:stat2data R Dataset:grinnellhouses

1495. Grocery Sales and Discounts

name:rdataset-stat2data-grocery reference:rdataset-stat2data-grocery’s home link. R package:stat2data R Dataset:grocery

1496. Are Gunnels Present at Shoreline?

name:rdataset-stat2data-gunnels reference:rdataset-stat2data-gunnels’s home link. R package:stat2data R Dataset:gunnels

1497. Guess Author’s Sex from Handwriting?

name:rdataset-stat2data-handwriting reference:rdataset-stat2data-handwriting’s home link. R package:stat2data R Dataset:handwriting

1498. Measurements on Three Hawk Species

name:rdataset-stat2data-hawks reference:rdataset-stat2data-hawks’s home link. R package:stat2data R Dataset:hawks

1499. Tail Lengths of Hawks

name:rdataset-stat2data-hawktail reference:rdataset-stat2data-hawktail’s home link. R package:stat2data R Dataset:hawktail

1500. Tail Lengths of Hawks (Unstacked)

name:rdataset-stat2data-hawktail2 reference:rdataset-stat2data-hawktail2’s home link. R package:stat2data R Dataset:hawktail2

1501. Correctly Identified Words in a Hearing Test

name:rdataset-stat2data-hearingtest reference:rdataset-stat2data-hearingtest’s home link. R package:stat2data R Dataset:hearingtest

1502. Heating Oil Consumption

name:rdataset-stat2data-heatingoil reference:rdataset-stat2data-heatingoil’s home link. R package:stat2data R Dataset:heatingoil

1503. Characteristics of Adirondack Hiking Trails

name:rdataset-stat2data-highpeaks reference:rdataset-stat2data-highpeaks’s home link. R package:stat2data R Dataset:highpeaks

1504. Grinnell College Basketball Games

name:rdataset-stat2data-hoops reference:rdataset-stat2data-hoops’s home link. R package:stat2data R Dataset:hoops

1505. Prices of Horses

name:rdataset-stat2data-horseprices reference:rdataset-stat2data-horseprices’s home link. R package:stat2data R Dataset:horseprices

1506. House Prices, Sizes, and Lot Areas

name:rdataset-stat2data-houses reference:rdataset-stat2data-houses’s home link. R package:stat2data R Dataset:houses

1507. House Prices in Rural NY

name:rdataset-stat2data-housesny reference:rdataset-stat2data-housesny’s home link. R package:stat2data R Dataset:housesny

1508. Intensive Care Unit Patients

name:rdataset-stat2data-icu reference:rdataset-stat2data-icu’s home link. R package:stat2data R Dataset:icu

1509. Infant Mortality Rates

name:rdataset-stat2data-infantmortality2010 reference:rdataset-stat2data-infantmortality2010’s home link. R package:stat2data R Dataset:infantmortality2010

1510. Monthly Consumer Price Index (2009-2016)

name:rdataset-stat2data-inflation reference:rdataset-stat2data-inflation’s home link. R package:stat2data R Dataset:inflation

1511. Congressional Votes on a Health Insurance Bill

name:rdataset-stat2data-insurancevote reference:rdataset-stat2data-insurancevote’s home link. R package:stat2data R Dataset:insurancevote

1512. Guess IQ from a Photo?

name:rdataset-stat2data-iqguessing reference:rdataset-stat2data-iqguessing’s home link. R package:stat2data R Dataset:iqguessing

1513. Reporting Rates for Jurors

name:rdataset-stat2data-jurors reference:rdataset-stat2data-jurors’s home link. R package:stat2data R Dataset:jurors

1514. Kershaw Pitch Data

name:rdataset-stat2data-kershaw reference:rdataset-stat2data-kershaw’s home link. R package:stat2data R Dataset:kershaw

1515. Key West Water Temperatures

name:rdataset-stat2data-keywestwater reference:rdataset-stat2data-keywestwater’s home link. R package:stat2data R Dataset:keywestwater

1516. Body Measurements of Children

name:rdataset-stat2data-kids198 reference:rdataset-stat2data-kids198’s home link. R package:stat2data R Dataset:kids198

1517. Leafhopper Diet and Longevity

name:rdataset-stat2data-leafhoppers reference:rdataset-stat2data-leafhoppers’s home link. R package:stat2data R Dataset:leafhoppers

1518. Leaf Measurements

name:rdataset-stat2data-leafwidth reference:rdataset-stat2data-leafwidth’s home link. R package:stat2data R Dataset:leafwidth

1519. Responses to Treatment for Leukemia

name:rdataset-stat2data-leukemia reference:rdataset-stat2data-leukemia’s home link. R package:stat2data R Dataset:leukemia

1520. Levee Failures along the Mississippi River

name:rdataset-stat2data-leveefailures reference:rdataset-stat2data-leveefailures’s home link. R package:stat2data R Dataset:leveefailures

1521. Lewy Bodies and Dimentia

name:rdataset-stat2data-lewybody2groups reference:rdataset-stat2data-lewybody2groups’s home link. R package:stat2data R Dataset:lewybody2groups

1522. Lewy Bodies and Dimentia with Alzheimer’s

name:rdataset-stat2data-lewydlbad reference:rdataset-stat2data-lewydlbad’s home link. R package:stat2data R Dataset:lewydlbad

1523. Olympic Men’s Long Jump Gold Medal Distance (1900 - 2008)

name:rdataset-stat2data-longjumpolympics reference:rdataset-stat2data-longjumpolympics’s home link. R package:stat2data R Dataset:longjumpolympics

1524. Olympic Men’s Long Jump Gold Medal Distance (1900 - 2016)

name:rdataset-stat2data-longjumpolympics2016 reference:rdataset-stat2data-longjumpolympics2016’s home link. R package:stat2data R Dataset:longjumpolympics2016

1525. Sleep Hours for Teenagers

name:rdataset-stat2data-losingsleep reference:rdataset-stat2data-losingsleep’s home link. R package:stat2data R Dataset:losingsleep

1526. Return Rates for “Lost” Letters

name:rdataset-stat2data-lostletter reference:rdataset-stat2data-lostletter’s home link. R package:stat2data R Dataset:lostletter

1527. Daily Training for a Marathon Runner

name:rdataset-stat2data-marathon reference:rdataset-stat2data-marathon’s home link. R package:stat2data R Dataset:marathon

1528. Daily Change in Dow Jones and Nikkei Stock Market Indices

name:rdataset-stat2data-markets reference:rdataset-stat2data-markets’s home link. R package:stat2data R Dataset:markets

1529. Enrollments in Math Courses

name:rdataset-stat2data-mathenrollment reference:rdataset-stat2data-mathenrollment’s home link. R package:stat2data R Dataset:mathenrollment

1530. Math Placement Exam Results

name:rdataset-stat2data-mathplacement reference:rdataset-stat2data-mathplacement’s home link. R package:stat2data R Dataset:mathplacement

1531. GPA and Medical School Admission

name:rdataset-stat2data-medgpa reference:rdataset-stat2data-medgpa’s home link. R package:stat2data R Dataset:medgpa

1532. Meniscus Repair Methods

name:rdataset-stat2data-meniscus reference:rdataset-stat2data-meniscus’s home link. R package:stat2data R Dataset:meniscus

1533. Mental Health Admissions

name:rdataset-stat2data-mentalhealth reference:rdataset-stat2data-mentalhealth’s home link. R package:stat2data R Dataset:mentalhealth

1534. Metabolic Rate of Caterpillars

name:rdataset-stat2data-metabolicrate reference:rdataset-stat2data-metabolicrate’s home link. R package:stat2data R Dataset:metabolicrate

1535. Commute Times

name:rdataset-stat2data-metrocommutes reference:rdataset-stat2data-metrocommutes’s home link. R package:stat2data R Dataset:metrocommutes

1536. Health Services in Metropolitan Areas

name:rdataset-stat2data-metrohealth83 reference:rdataset-stat2data-metrohealth83’s home link. R package:stat2data R Dataset:metrohealth83

1537. Migraines and TMS

name:rdataset-stat2data-migraines reference:rdataset-stat2data-migraines’s home link. R package:stat2data R Dataset:migraines

1538. Ethics and a Milgram Experiment

name:rdataset-stat2data-milgram reference:rdataset-stat2data-milgram’s home link. R package:stat2data R Dataset:milgram

1539. Standings and Team Statistics from the 2007 Baseball Season

name:rdataset-stat2data-mlb2007standings reference:rdataset-stat2data-mlb2007standings’s home link. R package:stat2data R Dataset:mlb2007standings

1540. MLB Standings in 2016

name:rdataset-stat2data-mlbstandings2016 reference:rdataset-stat2data-mlbstandings2016’s home link. R package:stat2data R Dataset:mlbstandings2016

1541. Moth Eggs

name:rdataset-stat2data-motheggs reference:rdataset-stat2data-motheggs’s home link. R package:stat2data R Dataset:motheggs

1542. Effects of Serotonin in Mice

name:rdataset-stat2data-mousebrain reference:rdataset-stat2data-mousebrain’s home link. R package:stat2data R Dataset:mousebrain

1543. Estimating Time with Different Music Playing

name:rdataset-stat2data-musictime reference:rdataset-stat2data-musictime’s home link. R package:stat2data R Dataset:musictime

1544. North Carolina Birth Records

name:rdataset-stat2data-ncbirths reference:rdataset-stat2data-ncbirths’s home link. R package:stat2data R Dataset:ncbirths

1545. NFL Standings for 2007 Regular Season

name:rdataset-stat2data-nfl2007standings reference:rdataset-stat2data-nfl2007standings’s home link. R package:stat2data R Dataset:nfl2007standings

1546. NFL Standings for 2016 Regular Season

name:rdataset-stat2data-nflstandings2016 reference:rdataset-stat2data-nflstandings2016’s home link. R package:stat2data R Dataset:nflstandings2016

1547. Nursing Homes

name:rdataset-stat2data-nursing reference:rdataset-stat2data-nursing’s home link. R package:stat2data R Dataset:nursing

1548. Effect of Ultrasound on Oil Deapsorbtion

name:rdataset-stat2data-oildeapsorbtion reference:rdataset-stat2data-oildeapsorbtion’s home link. R package:stat2data R Dataset:oildeapsorbtion

1549. Fenthion in Olive Oil

name:rdataset-stat2data-olives reference:rdataset-stat2data-olives’s home link. R package:stat2data R Dataset:olives

1550. Space Shuttle O-Rings

name:rdataset-stat2data-orings reference:rdataset-stat2data-orings’s home link. R package:stat2data R Dataset:orings

1551. Overdrawn Checking Account?

name:rdataset-stat2data-overdrawn reference:rdataset-stat2data-overdrawn’s home link. R package:stat2data R Dataset:overdrawn

1552. Size of Oysters

name:rdataset-stat2data-oysters reference:rdataset-stat2data-oysters’s home link. R package:stat2data R Dataset:oysters

1553. Palm Beach Butterfly Ballot

name:rdataset-stat2data-palmbeach reference:rdataset-stat2data-palmbeach’s home link. R package:stat2data R Dataset:palmbeach

1554. Monthly Peace Bridge Traffic ( 2003-2015)

name:rdataset-stat2data-peacebridge2003 reference:rdataset-stat2data-peacebridge2003’s home link. R package:stat2data R Dataset:peacebridge2003

1555. Monthly Peace Bridge Traffic ( 2012-2015)

name:rdataset-stat2data-peacebridge2012 reference:rdataset-stat2data-peacebridge2012’s home link. R package:stat2data R Dataset:peacebridge2012

1556. Pedometer Walking Data

name:rdataset-stat2data-pedometer reference:rdataset-stat2data-pedometer’s home link. R package:stat2data R Dataset:pedometer

1557. Perch Sizes

name:rdataset-stat2data-perch reference:rdataset-stat2data-perch’s home link. R package:stat2data R Dataset:perch

1558. Additives in Pig Feed

name:rdataset-stat2data-pigfeed reference:rdataset-stat2data-pigfeed’s home link. R package:stat2data R Dataset:pigfeed

1559. Measurements of Pine Tree Seedlings

name:rdataset-stat2data-pines reference:rdataset-stat2data-pines’s home link. R package:stat2data R Dataset:pines

1560. Dopamine levels with PKU in diets

name:rdataset-stat2data-pku reference:rdataset-stat2data-pku’s home link. R package:stat2data R Dataset:pku

1561. Political Behavior of College Students

name:rdataset-stat2data-political reference:rdataset-stat2data-political’s home link. R package:stat2data R Dataset:political

1562. 2008 U.S. Presidential Election Polls

name:rdataset-stat2data-pollster08 reference:rdataset-stat2data-pollster08’s home link. R package:stat2data R Dataset:pollster08

1563. Popcorn Popping Success

name:rdataset-stat2data-popcorn reference:rdataset-stat2data-popcorn’s home link. R package:stat2data R Dataset:popcorn

1564. Porsche and Jaguar Prices

name:rdataset-stat2data-porschejaguar reference:rdataset-stat2data-porschejaguar’s home link. R package:stat2data R Dataset:porschejaguar

1565. Porsche Prices

name:rdataset-stat2data-porscheprice reference:rdataset-stat2data-porscheprice’s home link. R package:stat2data R Dataset:porscheprice

1566. Pulse Rates and Exercise

name:rdataset-stat2data-pulse reference:rdataset-stat2data-pulse’s home link. R package:stat2data R Dataset:pulse

1567. Putting Success by Length (Long Form)

name:rdataset-stat2data-putts1 reference:rdataset-stat2data-putts1’s home link. R package:stat2data R Dataset:putts1

1568. Putting Success by Length (Short Form)

name:rdataset-stat2data-putts2 reference:rdataset-stat2data-putts2’s home link. R package:stat2data R Dataset:putts2

1569. Hypothetical Putting Data (Short Form)

name:rdataset-stat2data-putts3 reference:rdataset-stat2data-putts3’s home link. R package:stat2data R Dataset:putts3

1570. Racial Animus and City Demgraphics

name:rdataset-stat2data-racialanimus reference:rdataset-stat2data-racialanimus’s home link. R package:stat2data R Dataset:racialanimus

1571. Comparing Twins Ability to Clear Radioactive Particles

name:rdataset-stat2data-radioactivetwins reference:rdataset-stat2data-radioactivetwins’s home link. R package:stat2data R Dataset:radioactivetwins

1572. Homes in Northampton MA Near Rail Trails

name:rdataset-stat2data-railstrails reference:rdataset-stat2data-railstrails’s home link. R package:stat2data R Dataset:railstrails

1573. Measurements of Rectangles

name:rdataset-stat2data-rectangles reference:rdataset-stat2data-rectangles’s home link. R package:stat2data R Dataset:rectangles

1574. Religion and GDP for Countries

name:rdataset-stat2data-religiongdp reference:rdataset-stat2data-religiongdp’s home link. R package:stat2data R Dataset:religiongdp

1575. Pulse Rates at Various Times of Day

name:rdataset-stat2data-repeatedpulse reference:rdataset-stat2data-repeatedpulse’s home link. R package:stat2data R Dataset:repeatedpulse

1576. US Residual Oil Production (Quarterly 1983-2016)

name:rdataset-stat2data-residualoil reference:rdataset-stat2data-residualoil’s home link. R package:stat2data R Dataset:residualoil

1577. Yearly Contributions to a Supplemental Retirement Account

name:rdataset-stat2data-retirement reference:rdataset-stat2data-retirement’s home link. R package:stat2data R Dataset:retirement

1578. Firefighter Promotion Exam Scores

name:rdataset-stat2data-ricci reference:rdataset-stat2data-ricci’s home link. R package:stat2data R Dataset:ricci

1579. Elements in River Water Samples

name:rdataset-stat2data-riverelements reference:rdataset-stat2data-riverelements’s home link. R package:stat2data R Dataset:riverelements

1580. Iron in River Water Samples

name:rdataset-stat2data-riveriron reference:rdataset-stat2data-riveriron’s home link. R package:stat2data R Dataset:riveriron

1581. Field Goal Attempts in the NFL

name:rdataset-stat2data-samplefg reference:rdataset-stat2data-samplefg’s home link. R package:stat2data R Dataset:samplefg

1582. Ants on Sandwiches

name:rdataset-stat2data-sandwichants reference:rdataset-stat2data-sandwichants’s home link. R package:stat2data R Dataset:sandwichants

1583. SAT Scores and GPA

name:rdataset-stat2data-satgpa reference:rdataset-stat2data-satgpa’s home link. R package:stat2data R Dataset:satgpa

1584. Arctic Sea Ice (1979-2015)

name:rdataset-stat2data-seaice reference:rdataset-stat2data-seaice’s home link. R package:stat2data R Dataset:seaice

1585. Sea Slug Larvae

name:rdataset-stat2data-seaslugs reference:rdataset-stat2data-seaslugs’s home link. R package:stat2data R Dataset:seaslugs

1586. Shrew Heart Rates at Stages of Sleep

name:rdataset-stat2data-sleepingshrews reference:rdataset-stat2data-sleepingshrews’s home link. R package:stat2data R Dataset:sleepingshrews

1587. Sparrow Measurements

name:rdataset-stat2data-sparrows reference:rdataset-stat2data-sparrows’s home link. R package:stat2data R Dataset:sparrows

1588. Land Area and Mammal Species

name:rdataset-stat2data-speciesarea reference:rdataset-stat2data-speciesarea’s home link. R package:stat2data R Dataset:speciesarea

1589. Highway Fatality Rates (Yearly)

name:rdataset-stat2data-speed reference:rdataset-stat2data-speed’s home link. R package:stat2data R Dataset:speed

1590. Effects of Oxygen on Sugar Metabolism

name:rdataset-stat2data-sugarethanol reference:rdataset-stat2data-sugarethanol’s home link. R package:stat2data R Dataset:sugarethanol

1591. Suicide Attempts in Shandong, China

name:rdataset-stat2data-suicidechina reference:rdataset-stat2data-suicidechina’s home link. R package:stat2data R Dataset:suicidechina

1592. Attitudes Towards Swahili in Kenyan Schools

name:rdataset-stat2data-swahili reference:rdataset-stat2data-swahili’s home link. R package:stat2data R Dataset:swahili

1593. Effects of a Fungus on Tadpoles

name:rdataset-stat2data-tadpoles reference:rdataset-stat2data-tadpoles’s home link. R package:stat2data R Dataset:tadpoles

1594. Daily Prices of Three Tech Stocks

name:rdataset-stat2data-techstocks reference:rdataset-stat2data-techstocks’s home link. R package:stat2data R Dataset:techstocks

1595. State Teen Pregnancy Rates

name:rdataset-stat2data-teenpregnancy reference:rdataset-stat2data-teenpregnancy’s home link. R package:stat2data R Dataset:teenpregnancy

1596. Textbook Prices

name:rdataset-stat2data-textprices reference:rdataset-stat2data-textprices’s home link. R package:stat2data R Dataset:textprices

1597. US Senate Votes on Clarence Thomas Confirmation

name:rdataset-stat2data-thomasconfirmation reference:rdataset-stat2data-thomasconfirmation’s home link. R package:stat2data R Dataset:thomasconfirmation

1598. Prices of Three Used Car Models (2007)

name:rdataset-stat2data-threecars reference:rdataset-stat2data-threecars’s home link. R package:stat2data R Dataset:threecars

1599. Price, Age, and Mileage of Three Used Car Models

name:rdataset-stat2data-threecars2017 reference:rdataset-stat2data-threecars2017’s home link. R package:stat2data R Dataset:threecars2017

1600. Improve Chances of Getting a Tip?

name:rdataset-stat2data-tipjoke reference:rdataset-stat2data-tipjoke’s home link. R package:stat2data R Dataset:tipjoke

1601. Passengers on the Titanic

name:rdataset-stat2data-titanic reference:rdataset-stat2data-titanic’s home link. R package:stat2data R Dataset:titanic

1602. Migraines and TMS

name:rdataset-stat2data-tms reference:rdataset-stat2data-tms’s home link. R package:stat2data R Dataset:tms

1603. LaDainian Tomlinson Rushing Yards

name:rdataset-stat2data-tomlinsonrush reference:rdataset-stat2data-tomlinsonrush’s home link. R package:stat2data R Dataset:tomlinsonrush

1604. Comparing Twins Ability to Clear Radioactive Particles

name:rdataset-stat2data-twinslungs reference:rdataset-stat2data-twinslungs’s home link. R package:stat2data R Dataset:twinslungs

1605. Defense of Undoing OCD Symptoms in Psychotherapy

name:rdataset-stat2data-undoing reference:rdataset-stat2data-undoing’s home link. R package:stat2data R Dataset:undoing

1606. Price of US Stamps

name:rdataset-stat2data-usstamps reference:rdataset-stat2data-usstamps’s home link. R package:stat2data R Dataset:usstamps

1607. Visual versus Verbal Performance

name:rdataset-stat2data-visualverbal reference:rdataset-stat2data-visualverbal’s home link. R package:stat2data R Dataset:visualverbal

1608. Voltage Drop for a Discharging Capacitor

name:rdataset-stat2data-volts reference:rdataset-stat2data-volts’s home link. R package:stat2data R Dataset:volts

1609. Effects of Exercise on First Walking

name:rdataset-stat2data-walkingbabies reference:rdataset-stat2data-walkingbabies’s home link. R package:stat2data R Dataset:walkingbabies

1610. Did the Author Walk the Dogs Today?

name:rdataset-stat2data-walkthedogs reference:rdataset-stat2data-walkthedogs’s home link. R package:stat2data R Dataset:walkthedogs

1611. Do Financial Incentives Improve Weight Loss?

name:rdataset-stat2data-weightlossincentive reference:rdataset-stat2data-weightlossincentive’s home link. R package:stat2data R Dataset:weightlossincentive

1612. Do Financial Incentives Improve Weight Loss? (4 Months)

name:rdataset-stat2data-weightlossincentive4 reference:rdataset-stat2data-weightlossincentive4’s home link. R package:stat2data R Dataset:weightlossincentive4

1613. Do Financial Incentives Improve Weight Loss? (7 Months)

name:rdataset-stat2data-weightlossincentive7 reference:rdataset-stat2data-weightlossincentive7’s home link. R package:stat2data R Dataset:weightlossincentive7

1614. Whickham Health Study

name:rdataset-stat2data-whickham2 reference:rdataset-stat2data-whickham2’s home link. R package:stat2data R Dataset:whickham2

1615. Experiment on Word Memory

name:rdataset-stat2data-wordmemory reference:rdataset-stat2data-wordmemory’s home link. R package:stat2data R Dataset:wordmemory

1616. Words with Friends Scores

name:rdataset-stat2data-wordswithfriends reference:rdataset-stat2data-wordswithfriends’s home link. R package:stat2data R Dataset:wordswithfriends

1617. Moving Wet Objects with Wrinkled Fingers

name:rdataset-stat2data-wrinkle reference:rdataset-stat2data-wrinkle’s home link. R package:stat2data R Dataset:wrinkle

1618. Annual survey of health-risk youth behaviors

name:rdataset-stat2data-youthrisk reference:rdataset-stat2data-youthrisk’s home link. R package:stat2data R Dataset:youthrisk

1619. Riding with a Driver Who Has Been Drinking

name:rdataset-stat2data-youthrisk2007 reference:rdataset-stat2data-youthrisk2007’s home link. R package:stat2data R Dataset:youthrisk2007

1620. Youth Risk Survey

name:rdataset-stat2data-youthrisk2009 reference:rdataset-stat2data-youthrisk2009’s home link. R package:stat2data R Dataset:youthrisk2009

1621. Stand Your Ground Simpson’s Paradox

name:rdataset-stat2data-zimmerman reference:rdataset-stat2data-zimmerman’s home link. R package:stat2data R Dataset:zimmerman

1622. Statewide Crime Data (1993)

name:rdataset-stevedata-af_crime93 reference:rdataset-stevedata-af_crime93’s home link. R package:stevedata R Dataset:af_crime93

1623. LME Aluminum Premiums Data

name:rdataset-stevedata-aluminum_premiums reference:rdataset-stevedata-aluminum_premiums’s home link. R package:stevedata R Dataset:aluminum_premiums

1624. Major Party (Democrat, Republican) Thermometer Index Data (1978-2012)

name:rdataset-stevedata-anes_partytherms reference:rdataset-stevedata-anes_partytherms’s home link. R package:stevedata R Dataset:anes_partytherms

1625. Abortion Attitudes (ANES, 2012)

name:rdataset-stevedata-anes_prochoice reference:rdataset-stevedata-anes_prochoice’s home link. R package:stevedata R Dataset:anes_prochoice

1626. Simple Data for a Simple Model of Individual Voter Turnout (ANES, 1984)

name:rdataset-stevedata-anes_vote84 reference:rdataset-stevedata-anes_vote84’s home link. R package:stevedata R Dataset:anes_vote84

1627. NYSE Arca Steel Index data, 2017–present

name:rdataset-stevedata-arca reference:rdataset-stevedata-arca’s home link. R package:stevedata R Dataset:arca

1628. Arctic Sea Ice Extent Data, 1901-2015

name:rdataset-stevedata-arcticseaice reference:rdataset-stevedata-arcticseaice’s home link. R package:stevedata R Dataset:arcticseaice

1629. Simple Mean Tariff Rate for Argentina

name:rdataset-stevedata-arg_tariff reference:rdataset-stevedata-arg_tariff’s home link. R package:stevedata R Dataset:arg_tariff

1630. Aviation Safety Network Statistics, 1942-2019

name:rdataset-stevedata-asn_stats reference:rdataset-stevedata-asn_stats’s home link. R package:stevedata R Dataset:asn_stats

1631. Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate

name:rdataset-stevedata-cft15 reference:rdataset-stevedata-cft15’s home link. R package:stevedata R Dataset:cft15

1632. Daily Clemson Temperature Data

name:rdataset-stevedata-clemson_temps reference:rdataset-stevedata-clemson_temps’s home link. R package:stevedata R Dataset:clemson_temps

1633. Carbon Dioxide Emissions Data

name:rdataset-stevedata-co2emissions reference:rdataset-stevedata-co2emissions’s home link. R package:stevedata R Dataset:co2emissions

1634. Coffee Imports for Select Importing Countries

name:rdataset-stevedata-coffee_imports reference:rdataset-stevedata-coffee_imports’s home link. R package:stevedata R Dataset:coffee_imports

1635. The Primary Commodity Price for Coffee (Arabica, Robustas)

name:rdataset-stevedata-coffee_price reference:rdataset-stevedata-coffee_price’s home link. R package:stevedata R Dataset:coffee_price

1636. Education Expenditure Data (Chatterjee and Price, 1977)

name:rdataset-stevedata-cp77 reference:rdataset-stevedata-cp77’s home link. R package:stevedata R Dataset:cp77

1637. The Datasaurus Dozen

name:rdataset-stevedata-datasaurus reference:rdataset-stevedata-datasaurus’s home link. R package:stevedata R Dataset:datasaurus

1638. Are There Civics Returns to Education?

name:rdataset-stevedata-dee04 reference:rdataset-stevedata-dee04’s home link. R package:stevedata R Dataset:dee04

1639. Dow Jones Industrial Average, 1885-Present

name:rdataset-stevedata-djia reference:rdataset-stevedata-djia’s home link. R package:stevedata R Dataset:djia

1640. Casualties/Fatalities in the U.S. for Drunk-Driving, Suicide, and Terrorism

name:rdataset-stevedata-dst reference:rdataset-stevedata-dst’s home link. R package:stevedata R Dataset:dst

1641. The Effect of Special Preparation on SAT-V Scores in Eight Randomized Experiments

name:rdataset-stevedata-eight_schools reference:rdataset-stevedata-eight_schools’s home link. R package:stevedata R Dataset:eight_schools

1642. State-Level Education and Voter Turnout in 2016

name:rdataset-stevedata-election_turnout reference:rdataset-stevedata-election_turnout’s home link. R package:stevedata R Dataset:election_turnout

1643. Export Quality Data for Passenger Cars, 1963-2014

name:rdataset-stevedata-eq_passengercars reference:rdataset-stevedata-eq_passengercars’s home link. R package:stevedata R Dataset:eq_passengercars

1644. British Attitudes Toward Immigration (2018-19)

name:rdataset-stevedata-ess9gb reference:rdataset-stevedata-ess9gb’s home link. R package:stevedata R Dataset:ess9gb

1645. Trust in the Police in Belgium (European Social Survey, Round 5)

name:rdataset-stevedata-essbe5 reference:rdataset-stevedata-essbe5’s home link. R package:stevedata R Dataset:essbe5

1646. EU Member States (Current as of 2019)

name:rdataset-stevedata-eustates reference:rdataset-stevedata-eustates’s home link. R package:stevedata R Dataset:eustates

1647. Hypothetical (Fake) Data on Academic Performance

name:rdataset-stevedata-fakeapi reference:rdataset-stevedata-fakeapi’s home link. R package:stevedata R Dataset:fakeapi

1648. Fake Data for a Logistic Regression

name:rdataset-stevedata-fakelogit reference:rdataset-stevedata-fakelogit’s home link. R package:stevedata R Dataset:fakelogit

1649. Fake Data for a Time-Series Cross-Section

name:rdataset-stevedata-faketscs reference:rdataset-stevedata-faketscs’s home link. R package:stevedata R Dataset:faketscs

1650. Fake Data for a Time-Series

name:rdataset-stevedata-faketsd reference:rdataset-stevedata-faketsd’s home link. R package:stevedata R Dataset:faketsd

1651. Gun Homicide Rate per 100,000 People, by Country

name:rdataset-stevedata-ghp100k reference:rdataset-stevedata-ghp100k’s home link. R package:stevedata R Dataset:ghp100k

1652. Abortion Opinions in the General Social Survey

name:rdataset-stevedata-gss_abortion reference:rdataset-stevedata-gss_abortion’s home link. R package:stevedata R Dataset:gss_abortion

1653. Attitudes Toward National Spending in the General Social Survey (2018)

name:rdataset-stevedata-gss_spending reference:rdataset-stevedata-gss_spending’s home link. R package:stevedata R Dataset:gss_spending

1654. The Gender Pay Gap in the General Social Survey

name:rdataset-stevedata-gss_wages reference:rdataset-stevedata-gss_wages’s home link. R package:stevedata R Dataset:gss_wages

1655. School Expenditures and Test Scores for 50 States, 1994-95

name:rdataset-stevedata-guber99 reference:rdataset-stevedata-guber99’s home link. R package:stevedata R Dataset:guber99

1656. Illiteracy in the Population 10 Years Old and Over, 1930

name:rdataset-stevedata-illiteracy30 reference:rdataset-stevedata-illiteracy30’s home link. R package:stevedata R Dataset:illiteracy30

1657. Land-Ocean Temperature Index, 1880-2020

name:rdataset-stevedata-loti reference:rdataset-stevedata-loti’s home link. R package:stevedata R Dataset:loti

1658. Long-Term Price Trends for Computers, TVs, and Related Items

name:rdataset-stevedata-ltpt reference:rdataset-stevedata-ltpt’s home link. R package:stevedata R Dataset:ltpt

1659. “Let Them Watch TV”

name:rdataset-stevedata-ltwt reference:rdataset-stevedata-ltwt’s home link. R package:stevedata R Dataset:ltwt

1660. History of Federal Minimum Wage Rates Under the Fair Labor Standards Act, 1938-2009

name:rdataset-stevedata-min_wage reference:rdataset-stevedata-min_wage’s home link. R package:stevedata R Dataset:min_wage

1661. Minimum Legal Drinking Age Fatalities Data

name:rdataset-stevedata-mm_mlda reference:rdataset-stevedata-mm_mlda’s home link. R package:stevedata R Dataset:mm_mlda

1662. Data from the 2009 National Health Interview Survey (NHIS)

name:rdataset-stevedata-mm_nhis reference:rdataset-stevedata-mm_nhis’s home link. R package:stevedata R Dataset:mm_nhis

1663. Motor Vehicle Production by Country, 1950-2019

name:rdataset-stevedata-mvprod reference:rdataset-stevedata-mvprod’s home link. R package:stevedata R Dataset:mvprod

1664. The Usual Daily Drinking Habits of Americans (NESARC, 2001-2)

name:rdataset-stevedata-nesarc_drinkspd reference:rdataset-stevedata-nesarc_drinkspd’s home link. R package:stevedata R Dataset:nesarc_drinkspd

1665. Medical-Care Expenditure: A Cross-National Survey (Newhouse, 1977)

name:rdataset-stevedata-newhouse77 reference:rdataset-stevedata-newhouse77’s home link. R package:stevedata R Dataset:newhouse77

1666. Ozone Depleting Gas Index Data, 1992-2019

name:rdataset-stevedata-odgi reference:rdataset-stevedata-odgi’s home link. R package:stevedata R Dataset:odgi

1667. U.S. Presidents and Their Terms in Office

name:rdataset-stevedata-presidents reference:rdataset-stevedata-presidents’s home link. R package:stevedata R Dataset:presidents

1668. Penn World Table (9.1) Macroeconomic Data for Select Countries, 1950-2017

name:rdataset-stevedata-pwt_sample reference:rdataset-stevedata-pwt_sample’s home link. R package:stevedata R Dataset:pwt_sample

1669. Anscombe’s (1973) Quartets

name:rdataset-stevedata-quartets reference:rdataset-stevedata-quartets’s home link. R package:stevedata R Dataset:quartets

1670. United States Recessions, 1855-present

name:rdataset-stevedata-recessions reference:rdataset-stevedata-recessions’s home link. R package:stevedata R Dataset:recessions

1671. Systemic Banking Crises Database II

name:rdataset-stevedata-sbcd reference:rdataset-stevedata-sbcd’s home link. R package:stevedata R Dataset:sbcd

1672. South Carolina County GOP/Democratic Primary Data, 2016

name:rdataset-stevedata-scp16 reference:rdataset-stevedata-scp16’s home link. R package:stevedata R Dataset:scp16

1673. Global Average Absolute Sea Level Change, 1880–2015

name:rdataset-stevedata-sealevels reference:rdataset-stevedata-sealevels’s home link. R package:stevedata R Dataset:sealevels

1674. Sulfur Dioxide Emissions, 1980-2020

name:rdataset-stevedata-so2concentrations reference:rdataset-stevedata-so2concentrations’s home link. R package:stevedata R Dataset:so2concentrations

1675. Steve’s (Professional) Clothes, as of March 20, 2022

name:rdataset-stevedata-steves_clothes reference:rdataset-stevedata-steves_clothes’s home link. R package:stevedata R Dataset:steves_clothes

1676. IMF Primary Commodity Price Data for Sugar

name:rdataset-stevedata-sugar_price reference:rdataset-stevedata-sugar_price’s home link. R package:stevedata R Dataset:sugar_price

1677. Margaret Thatcher Satisfaction Ratings, 1980-1990

name:rdataset-stevedata-thatcher_approval reference:rdataset-stevedata-thatcher_approval’s home link. R package:stevedata R Dataset:thatcher_approval

1678. Thermometer Ratings for Donald Trump and Barack Obama

name:rdataset-stevedata-therms reference:rdataset-stevedata-therms’s home link. R package:stevedata R Dataset:therms

1679. Turnip prices in Animal Crossing (New Horizons)

name:rdataset-stevedata-turnips reference:rdataset-stevedata-turnips’s home link. R package:stevedata R Dataset:turnips

1680. The Individual Correlates of the Trump Vote in 2016

name:rdataset-stevedata-tv16 reference:rdataset-stevedata-tv16’s home link. R package:stevedata R Dataset:tv16

1681. United Kingdom Effective Exchange Rate Index Data, 1990-2019

name:rdataset-stevedata-ukg_eeri reference:rdataset-stevedata-ukg_eeri’s home link. R package:stevedata R Dataset:ukg_eeri

1682. Cross-National Rates of Trade Union Density

name:rdataset-stevedata-uniondensity reference:rdataset-stevedata-uniondensity’s home link. R package:stevedata R Dataset:uniondensity

1683. United States-China GDP and GDP Forecasts, 1960-2050

name:rdataset-stevedata-usa_chn_gdp_forecasts reference:rdataset-stevedata-usa_chn_gdp_forecasts’s home link. R package:stevedata R Dataset:usa_chn_gdp_forecasts

1684. Percentage of U.S. Households with Computer Access, by Year

name:rdataset-stevedata-usa_computers reference:rdataset-stevedata-usa_computers’s home link. R package:stevedata R Dataset:usa_computers

1685. U.S. Inbound/Outbound Migration Data, 1990-2017

name:rdataset-stevedata-usa_migration reference:rdataset-stevedata-usa_migration’s home link. R package:stevedata R Dataset:usa_migration

1686. State Abbreviations, Names, and Regions/Divisions

name:rdataset-stevedata-usa_states reference:rdataset-stevedata-usa_states’s home link. R package:stevedata R Dataset:usa_states

1687. U.S. Trade and GDP, 1790-2018

name:rdataset-stevedata-usa_tradegdp reference:rdataset-stevedata-usa_tradegdp’s home link. R package:stevedata R Dataset:usa_tradegdp

1688. Sample Turnout and Demographic Data from the 2000 Current Population Survey

name:rdataset-stevedata-voteincome reference:rdataset-stevedata-voteincome’s home link. R package:stevedata R Dataset:voteincome

1689. Syncing Word Values Survey Country Codes with CoW Codes

name:rdataset-stevedata-wvs_ccodes reference:rdataset-stevedata-wvs_ccodes’s home link. R package:stevedata R Dataset:wvs_ccodes

1690. Attitudes about Immigration in the World Values Survey

name:rdataset-stevedata-wvs_immig reference:rdataset-stevedata-wvs_immig’s home link. R package:stevedata R Dataset:wvs_immig

1691. Attitudes about the Justifiability of Bribe-Taking in the World Values Survey

name:rdataset-stevedata-wvs_justifbribe reference:rdataset-stevedata-wvs_justifbribe’s home link. R package:stevedata R Dataset:wvs_justifbribe

1692. Attitudes on the Justifiability of Abortion in the United States (World Values Survey, 1982-2011)

name:rdataset-stevedata-wvs_usa_abortion reference:rdataset-stevedata-wvs_usa_abortion’s home link. R package:stevedata R Dataset:wvs_usa_abortion

1693. Education Categories for the United States in the World Values Survey

name:rdataset-stevedata-wvs_usa_educat reference:rdataset-stevedata-wvs_usa_educat’s home link. R package:stevedata R Dataset:wvs_usa_educat

1694. Region Categories for the United States in the World Values Survey

name:rdataset-stevedata-wvs_usa_regions reference:rdataset-stevedata-wvs_usa_regions’s home link. R package:stevedata R Dataset:wvs_usa_regions

1695. Yugo Sales in the United States, 1985-1992

name:rdataset-stevedata-yugo_sales reference:rdataset-stevedata-yugo_sales’s home link. R package:stevedata R Dataset:yugo_sales

1696. NCCTG Lung Cancer Data

name:rdataset-survival-cancer reference:rdataset-survival-cancer’s home link. R package:survival R Dataset:cancer

1697. Chronic Granulotamous Disease data

name:rdataset-survival-cgd reference:rdataset-survival-cgd’s home link. R package:survival R Dataset:cgd

1698. Ddiabetic retinopathy

name:rdataset-survival-diabetic reference:rdataset-survival-diabetic’s home link. R package:survival R Dataset:diabetic

1699. Assay of serum free light chain for 7874 subjects.

name:rdataset-survival-flchain reference:rdataset-survival-flchain’s home link. R package:survival R Dataset:flchain

1700. Stanford Heart Transplant data

name:rdataset-survival-heart reference:rdataset-survival-heart’s home link. R package:survival R Dataset:heart

1701. Data from the 1972-78 GSS data used by Logan

name:rdataset-survival-logan reference:rdataset-survival-logan’s home link. R package:survival R Dataset:logan

1702. Data from the National Wilm’s Tumor Study

name:rdataset-survival-nwtco reference:rdataset-survival-nwtco’s home link. R package:survival R Dataset:nwtco

1703. Mayo Clinic Primary Biliary Cholangitis Data

name:rdataset-survival-pbc reference:rdataset-survival-pbc’s home link. R package:survival R Dataset:pbc

1704. Diabetic Retinopathy

name:rdataset-survival-retinopathy reference:rdataset-survival-retinopathy’s home link. R package:survival R Dataset:retinopathy

1705. rhDNASE data set

name:rdataset-survival-rhdnase reference:rdataset-survival-rhdnase’s home link. R package:survival R Dataset:rhdnase

1706. Data from a soldering experiment

name:rdataset-survival-solder reference:rdataset-survival-solder’s home link. R package:survival R Dataset:solder

1707. Tobin’s Tobit data

name:rdataset-survival-tobin reference:rdataset-survival-tobin’s home link. R package:survival R Dataset:tobin

1708. Liver transplant waiting list

name:rdataset-survival-transplant reference:rdataset-survival-transplant’s home link. R package:survival R Dataset:transplant

1709. Data from a trial of usrodeoxycholic acid

name:rdataset-survival-udca reference:rdataset-survival-udca’s home link. R package:survival R Dataset:udca

1710. Liver related laboratory data

name:rdataset-texmex-liver reference:rdataset-texmex-liver’s home link. R package:texmex R Dataset:liver

1711. Rain, wavesurge, portpirie and nidd datasets.

name:rdataset-texmex-nidd reference:rdataset-texmex-nidd’s home link. R package:texmex R Dataset:nidd

1712. Rain, wavesurge, portpirie and nidd datasets.

name:rdataset-texmex-portpirie reference:rdataset-texmex-portpirie’s home link. R package:texmex R Dataset:portpirie

1713. Rain, wavesurge, portpirie and nidd datasets.

name:rdataset-texmex-rain reference:rdataset-texmex-rain’s home link. R package:texmex R Dataset:rain

1714. Air pollution data, separately for summer and winter months

name:rdataset-texmex-summer reference:rdataset-texmex-summer’s home link. R package:texmex R Dataset:summer

1715. Rain, wavesurge, portpirie and nidd datasets.

name:rdataset-texmex-wavesurge reference:rdataset-texmex-wavesurge’s home link. R package:texmex R Dataset:wavesurge

1716. Air pollution data, separately for summer and winter months

name:rdataset-texmex-winter reference:rdataset-texmex-winter’s home link. R package:texmex R Dataset:winter

1717. Song rankings for Billboard top 100 in the year 2000

name:rdataset-tidyr-billboard reference:rdataset-tidyr-billboard’s home link. R package:tidyr R Dataset:billboard

1718. Completed construction in the US in 2018

name:rdataset-tidyr-construction reference:rdataset-tidyr-construction’s home link. R package:tidyr R Dataset:construction

1719. Fish encounters

name:rdataset-tidyr-fish_encounters reference:rdataset-tidyr-fish_encounters’s home link. R package:tidyr R Dataset:fish_encounters

1720. World Health Organization TB data

name:rdataset-tidyr-population reference:rdataset-tidyr-population’s home link. R package:tidyr R Dataset:population

1721. Pew religion and income survey

name:rdataset-tidyr-relig_income reference:rdataset-tidyr-relig_income’s home link. R package:tidyr R Dataset:relig_income

1722. Some data about the Smith family

name:rdataset-tidyr-smiths reference:rdataset-tidyr-smiths’s home link. R package:tidyr R Dataset:smiths

1723. Example tabular representations

name:rdataset-tidyr-table1 reference:rdataset-tidyr-table1’s home link. R package:tidyr R Dataset:table1

1724. Example tabular representations

name:rdataset-tidyr-table2 reference:rdataset-tidyr-table2’s home link. R package:tidyr R Dataset:table2

1725. Example tabular representations

name:rdataset-tidyr-table3 reference:rdataset-tidyr-table3’s home link. R package:tidyr R Dataset:table3

1726. Example tabular representations

name:rdataset-tidyr-table4a reference:rdataset-tidyr-table4a’s home link. R package:tidyr R Dataset:table4a

1727. Example tabular representations

name:rdataset-tidyr-table4b reference:rdataset-tidyr-table4b’s home link. R package:tidyr R Dataset:table4b

1728. Example tabular representations

name:rdataset-tidyr-table5 reference:rdataset-tidyr-table5’s home link. R package:tidyr R Dataset:table5

1729. US rent and income data

name:rdataset-tidyr-us_rent_income reference:rdataset-tidyr-us_rent_income’s home link. R package:tidyr R Dataset:us_rent_income

1730. World Health Organization TB data

name:rdataset-tidyr-who reference:rdataset-tidyr-who’s home link. R package:tidyr R Dataset:who

1731. Population data from the world bank

name:rdataset-tidyr-world_bank_pop reference:rdataset-tidyr-world_bank_pop’s home link. R package:tidyr R Dataset:world_bank_pop

1732. NACE classification code table

name:rdataset-validate-nace_rev2 reference:rdataset-validate-nace_rev2’s home link. R package:validate R Dataset:nace_rev2

1733. data on Dutch supermarkets

name:rdataset-validate-retailers reference:rdataset-validate-retailers’s home link. R package:validate R Dataset:retailers

1734. Economic data on Samplonia

name:rdataset-validate-samplonomy reference:rdataset-validate-samplonomy’s home link. R package:validate R Dataset:samplonomy

1735. data on Dutch supermarkets

name:rdataset-validate-sbs2000 reference:rdataset-validate-sbs2000’s home link. R package:validate R Dataset:sbs2000

1736. Arthritis Treatment Data

name:rdataset-vcd-arthritis reference:rdataset-vcd-arthritis’s home link. R package:vcd R Dataset:arthritis

1737. Baseball Data

name:rdataset-vcd-baseball reference:rdataset-vcd-baseball’s home link. R package:vcd R Dataset:baseball

1738. Broken Marriage Data

name:rdataset-vcd-brokenmarriage reference:rdataset-vcd-brokenmarriage’s home link. R package:vcd R Dataset:brokenmarriage

1739. Ergebnisse der Fussball-Bundesliga

name:rdataset-vcd-bundesliga reference:rdataset-vcd-bundesliga’s home link. R package:vcd R Dataset:bundesliga

1740. Votes in German Bundestag Election 2005

name:rdataset-vcd-bundestag2005 reference:rdataset-vcd-bundestag2005’s home link. R package:vcd R Dataset:bundestag2005

1741. Butterfly Species in Malaya

name:rdataset-vcd-butterfly reference:rdataset-vcd-butterfly’s home link. R package:vcd R Dataset:butterfly

1742. Breathlessness and Wheeze in Coal Miners

name:rdataset-vcd-coalminers reference:rdataset-vcd-coalminers’s home link. R package:vcd R Dataset:coalminers

1743. Danish Welfare Study Data

name:rdataset-vcd-danishwelfare reference:rdataset-vcd-danishwelfare’s home link. R package:vcd R Dataset:danishwelfare

1744. Employment Status

name:rdataset-vcd-employment reference:rdataset-vcd-employment’s home link. R package:vcd R Dataset:employment

1745. ‘May’ in Federalist Papers

name:rdataset-vcd-federalist reference:rdataset-vcd-federalist’s home link. R package:vcd R Dataset:federalist

1746. Hitters Data

name:rdataset-vcd-hitters reference:rdataset-vcd-hitters’s home link. R package:vcd R Dataset:hitters

1747. Death by Horse Kicks

name:rdataset-vcd-horsekicks reference:rdataset-vcd-horsekicks’s home link. R package:vcd R Dataset:horsekicks

1748. Hospital data

name:rdataset-vcd-hospital reference:rdataset-vcd-hospital’s home link. R package:vcd R Dataset:hospital

1749. Job Satisfaction Data

name:rdataset-vcd-jobsatisfaction reference:rdataset-vcd-jobsatisfaction’s home link. R package:vcd R Dataset:jobsatisfaction

1750. Opinions About Joint Sports

name:rdataset-vcd-jointsports reference:rdataset-vcd-jointsports’s home link. R package:vcd R Dataset:jointsports

1751. Lifeboats on the Titanic

name:rdataset-vcd-lifeboats reference:rdataset-vcd-lifeboats’s home link. R package:vcd R Dataset:lifeboats

1752. Diagnosis of Multiple Sclerosis

name:rdataset-vcd-mspatients reference:rdataset-vcd-mspatients’s home link. R package:vcd R Dataset:mspatients

1753. Non-Response Survey Data

name:rdataset-vcd-nonresponse reference:rdataset-vcd-nonresponse’s home link. R package:vcd R Dataset:nonresponse

1754. Ovary Cancer Data

name:rdataset-vcd-ovarycancer reference:rdataset-vcd-ovarycancer’s home link. R package:vcd R Dataset:ovarycancer

1755. Pre-marital Sex and Divorce

name:rdataset-vcd-presex reference:rdataset-vcd-presex’s home link. R package:vcd R Dataset:presex

1756. Corporal Punishment Data

name:rdataset-vcd-punishment reference:rdataset-vcd-punishment’s home link. R package:vcd R Dataset:punishment

1757. Repeat Victimization Data

name:rdataset-vcd-repvict reference:rdataset-vcd-repvict’s home link. R package:vcd R Dataset:repvict

1758. Rochdale Data

name:rdataset-vcd-rochdale reference:rdataset-vcd-rochdale’s home link. R package:vcd R Dataset:rochdale

1759. Families in Saxony

name:rdataset-vcd-saxony reference:rdataset-vcd-saxony’s home link. R package:vcd R Dataset:saxony

1760. Sex is Fun

name:rdataset-vcd-sexualfun reference:rdataset-vcd-sexualfun’s home link. R package:vcd R Dataset:sexualfun

1761. Space Shuttle O-ring Failures

name:rdataset-vcd-spaceshuttle reference:rdataset-vcd-spaceshuttle’s home link. R package:vcd R Dataset:spaceshuttle

1762. Suicide Rates in Germany

name:rdataset-vcd-suicide reference:rdataset-vcd-suicide’s home link. R package:vcd R Dataset:suicide

1763. Truck Accidents Data

name:rdataset-vcd-trucks reference:rdataset-vcd-trucks’s home link. R package:vcd R Dataset:trucks

1764. UK Soccer Scores

name:rdataset-vcd-uksoccer reference:rdataset-vcd-uksoccer’s home link. R package:vcd R Dataset:uksoccer

1765. Visual Acuity in Left and Right Eyes

name:rdataset-vcd-visualacuity reference:rdataset-vcd-visualacuity’s home link. R package:vcd R Dataset:visualacuity

1766. Von Bortkiewicz Horse Kicks Data

name:rdataset-vcd-vonbort reference:rdataset-vcd-vonbort’s home link. R package:vcd R Dataset:vonbort

1767. Weldon’s Dice Data

name:rdataset-vcd-weldondice reference:rdataset-vcd-weldondice’s home link. R package:vcd R Dataset:weldondice

1768. Women in Queues

name:rdataset-vcd-womenqueue reference:rdataset-vcd-womenqueue’s home link. R package:vcd R Dataset:womenqueue

1769. admnrev

name:rdataset-wooldridge-admnrev reference:rdataset-wooldridge-admnrev’s home link. R package:wooldridge R Dataset:admnrev

1770. affairs

name:rdataset-wooldridge-affairs reference:rdataset-wooldridge-affairs’s home link. R package:wooldridge R Dataset:affairs

1771. airfare

name:rdataset-wooldridge-airfare reference:rdataset-wooldridge-airfare’s home link. R package:wooldridge R Dataset:airfare

1772. alcohol

name:rdataset-wooldridge-alcohol reference:rdataset-wooldridge-alcohol’s home link. R package:wooldridge R Dataset:alcohol

1773. apple

name:rdataset-wooldridge-apple reference:rdataset-wooldridge-apple’s home link. R package:wooldridge R Dataset:apple

1774. approval

name:rdataset-wooldridge-approval reference:rdataset-wooldridge-approval’s home link. R package:wooldridge R Dataset:approval

1775. athlet1

name:rdataset-wooldridge-athlet1 reference:rdataset-wooldridge-athlet1’s home link. R package:wooldridge R Dataset:athlet1

1776. athlet2

name:rdataset-wooldridge-athlet2 reference:rdataset-wooldridge-athlet2’s home link. R package:wooldridge R Dataset:athlet2

1777. attend

name:rdataset-wooldridge-attend reference:rdataset-wooldridge-attend’s home link. R package:wooldridge R Dataset:attend

1778. audit

name:rdataset-wooldridge-audit reference:rdataset-wooldridge-audit’s home link. R package:wooldridge R Dataset:audit

1779. barium

name:rdataset-wooldridge-barium reference:rdataset-wooldridge-barium’s home link. R package:wooldridge R Dataset:barium

1780. beauty

name:rdataset-wooldridge-beauty reference:rdataset-wooldridge-beauty’s home link. R package:wooldridge R Dataset:beauty

1781. benefits

name:rdataset-wooldridge-benefits reference:rdataset-wooldridge-benefits’s home link. R package:wooldridge R Dataset:benefits

1782. beveridge

name:rdataset-wooldridge-beveridge reference:rdataset-wooldridge-beveridge’s home link. R package:wooldridge R Dataset:beveridge

1783. big9salary

name:rdataset-wooldridge-big9salary reference:rdataset-wooldridge-big9salary’s home link. R package:wooldridge R Dataset:big9salary

1784. bwght

name:rdataset-wooldridge-bwght reference:rdataset-wooldridge-bwght’s home link. R package:wooldridge R Dataset:bwght

1785. bwght2

name:rdataset-wooldridge-bwght2 reference:rdataset-wooldridge-bwght2’s home link. R package:wooldridge R Dataset:bwght2

1786. campus

name:rdataset-wooldridge-campus reference:rdataset-wooldridge-campus’s home link. R package:wooldridge R Dataset:campus

1787. card

name:rdataset-wooldridge-card reference:rdataset-wooldridge-card’s home link. R package:wooldridge R Dataset:card

1788. catholic

name:rdataset-wooldridge-catholic reference:rdataset-wooldridge-catholic’s home link. R package:wooldridge R Dataset:catholic

1789. cement

name:rdataset-wooldridge-cement reference:rdataset-wooldridge-cement’s home link. R package:wooldridge R Dataset:cement

1790. census2000

name:rdataset-wooldridge-census2000 reference:rdataset-wooldridge-census2000’s home link. R package:wooldridge R Dataset:census2000

1791. ceosal1

name:rdataset-wooldridge-ceosal1 reference:rdataset-wooldridge-ceosal1’s home link. R package:wooldridge R Dataset:ceosal1

1792. ceosal2

name:rdataset-wooldridge-ceosal2 reference:rdataset-wooldridge-ceosal2’s home link. R package:wooldridge R Dataset:ceosal2

1793. charity

name:rdataset-wooldridge-charity reference:rdataset-wooldridge-charity’s home link. R package:wooldridge R Dataset:charity

1794. consump

name:rdataset-wooldridge-consump reference:rdataset-wooldridge-consump’s home link. R package:wooldridge R Dataset:consump

1795. corn

name:rdataset-wooldridge-corn reference:rdataset-wooldridge-corn’s home link. R package:wooldridge R Dataset:corn

1796. countymurders

name:rdataset-wooldridge-countymurders reference:rdataset-wooldridge-countymurders’s home link. R package:wooldridge R Dataset:countymurders

1797. cps78_85

name:rdataset-wooldridge-cps78_85 reference:rdataset-wooldridge-cps78_85’s home link. R package:wooldridge R Dataset:cps78_85

1798. cps91

name:rdataset-wooldridge-cps91 reference:rdataset-wooldridge-cps91’s home link. R package:wooldridge R Dataset:cps91

1799. crime1

name:rdataset-wooldridge-crime1 reference:rdataset-wooldridge-crime1’s home link. R package:wooldridge R Dataset:crime1

1800. crime2

name:rdataset-wooldridge-crime2 reference:rdataset-wooldridge-crime2’s home link. R package:wooldridge R Dataset:crime2

1801. crime3

name:rdataset-wooldridge-crime3 reference:rdataset-wooldridge-crime3’s home link. R package:wooldridge R Dataset:crime3

1802. crime4

name:rdataset-wooldridge-crime4 reference:rdataset-wooldridge-crime4’s home link. R package:wooldridge R Dataset:crime4

1803. discrim

name:rdataset-wooldridge-discrim reference:rdataset-wooldridge-discrim’s home link. R package:wooldridge R Dataset:discrim

1804. driving

name:rdataset-wooldridge-driving reference:rdataset-wooldridge-driving’s home link. R package:wooldridge R Dataset:driving

1805. earns

name:rdataset-wooldridge-earns reference:rdataset-wooldridge-earns’s home link. R package:wooldridge R Dataset:earns

1806. econmath

name:rdataset-wooldridge-econmath reference:rdataset-wooldridge-econmath’s home link. R package:wooldridge R Dataset:econmath

1807. elem94_95

name:rdataset-wooldridge-elem94_95 reference:rdataset-wooldridge-elem94_95’s home link. R package:wooldridge R Dataset:elem94_95

1808. engin

name:rdataset-wooldridge-engin reference:rdataset-wooldridge-engin’s home link. R package:wooldridge R Dataset:engin

1809. expendshares

name:rdataset-wooldridge-expendshares reference:rdataset-wooldridge-expendshares’s home link. R package:wooldridge R Dataset:expendshares

1810. ezanders

name:rdataset-wooldridge-ezanders reference:rdataset-wooldridge-ezanders’s home link. R package:wooldridge R Dataset:ezanders

1811. ezunem

name:rdataset-wooldridge-ezunem reference:rdataset-wooldridge-ezunem’s home link. R package:wooldridge R Dataset:ezunem

1812. fair

name:rdataset-wooldridge-fair reference:rdataset-wooldridge-fair’s home link. R package:wooldridge R Dataset:fair

1813. fertil1

name:rdataset-wooldridge-fertil1 reference:rdataset-wooldridge-fertil1’s home link. R package:wooldridge R Dataset:fertil1

1814. fertil2

name:rdataset-wooldridge-fertil2 reference:rdataset-wooldridge-fertil2’s home link. R package:wooldridge R Dataset:fertil2

1815. fertil3

name:rdataset-wooldridge-fertil3 reference:rdataset-wooldridge-fertil3’s home link. R package:wooldridge R Dataset:fertil3

1816. fish

name:rdataset-wooldridge-fish reference:rdataset-wooldridge-fish’s home link. R package:wooldridge R Dataset:fish

1817. fringe

name:rdataset-wooldridge-fringe reference:rdataset-wooldridge-fringe’s home link. R package:wooldridge R Dataset:fringe

1818. gpa1

name:rdataset-wooldridge-gpa1 reference:rdataset-wooldridge-gpa1’s home link. R package:wooldridge R Dataset:gpa1

1819. gpa2

name:rdataset-wooldridge-gpa2 reference:rdataset-wooldridge-gpa2’s home link. R package:wooldridge R Dataset:gpa2

1820. gpa3

name:rdataset-wooldridge-gpa3 reference:rdataset-wooldridge-gpa3’s home link. R package:wooldridge R Dataset:gpa3

1821. happiness

name:rdataset-wooldridge-happiness reference:rdataset-wooldridge-happiness’s home link. R package:wooldridge R Dataset:happiness

1822. hprice1

name:rdataset-wooldridge-hprice1 reference:rdataset-wooldridge-hprice1’s home link. R package:wooldridge R Dataset:hprice1

1823. hprice2

name:rdataset-wooldridge-hprice2 reference:rdataset-wooldridge-hprice2’s home link. R package:wooldridge R Dataset:hprice2

1824. hprice3

name:rdataset-wooldridge-hprice3 reference:rdataset-wooldridge-hprice3’s home link. R package:wooldridge R Dataset:hprice3

1825. hseinv

name:rdataset-wooldridge-hseinv reference:rdataset-wooldridge-hseinv’s home link. R package:wooldridge R Dataset:hseinv

1826. htv

name:rdataset-wooldridge-htv reference:rdataset-wooldridge-htv’s home link. R package:wooldridge R Dataset:htv

1827. infmrt

name:rdataset-wooldridge-infmrt reference:rdataset-wooldridge-infmrt’s home link. R package:wooldridge R Dataset:infmrt

1828. injury

name:rdataset-wooldridge-injury reference:rdataset-wooldridge-injury’s home link. R package:wooldridge R Dataset:injury

1829. intdef

name:rdataset-wooldridge-intdef reference:rdataset-wooldridge-intdef’s home link. R package:wooldridge R Dataset:intdef

1830. intqrt

name:rdataset-wooldridge-intqrt reference:rdataset-wooldridge-intqrt’s home link. R package:wooldridge R Dataset:intqrt

1831. inven

name:rdataset-wooldridge-inven reference:rdataset-wooldridge-inven’s home link. R package:wooldridge R Dataset:inven

1832. jtrain

name:rdataset-wooldridge-jtrain reference:rdataset-wooldridge-jtrain’s home link. R package:wooldridge R Dataset:jtrain

1833. jtrain2

name:rdataset-wooldridge-jtrain2 reference:rdataset-wooldridge-jtrain2’s home link. R package:wooldridge R Dataset:jtrain2

1834. jtrain3

name:rdataset-wooldridge-jtrain3 reference:rdataset-wooldridge-jtrain3’s home link. R package:wooldridge R Dataset:jtrain3

1835. jtrain98

name:rdataset-wooldridge-jtrain98 reference:rdataset-wooldridge-jtrain98’s home link. R package:wooldridge R Dataset:jtrain98

1836. k401k

name:rdataset-wooldridge-k401k reference:rdataset-wooldridge-k401k’s home link. R package:wooldridge R Dataset:k401k

1837. k401ksubs

name:rdataset-wooldridge-k401ksubs reference:rdataset-wooldridge-k401ksubs’s home link. R package:wooldridge R Dataset:k401ksubs

1838. kielmc

name:rdataset-wooldridge-kielmc reference:rdataset-wooldridge-kielmc’s home link. R package:wooldridge R Dataset:kielmc

1839. labsup

name:rdataset-wooldridge-labsup reference:rdataset-wooldridge-labsup’s home link. R package:wooldridge R Dataset:labsup

1840. lawsch85

name:rdataset-wooldridge-lawsch85 reference:rdataset-wooldridge-lawsch85’s home link. R package:wooldridge R Dataset:lawsch85

1841. loanapp

name:rdataset-wooldridge-loanapp reference:rdataset-wooldridge-loanapp’s home link. R package:wooldridge R Dataset:loanapp

1842. lowbrth

name:rdataset-wooldridge-lowbrth reference:rdataset-wooldridge-lowbrth’s home link. R package:wooldridge R Dataset:lowbrth

1843. mathpnl

name:rdataset-wooldridge-mathpnl reference:rdataset-wooldridge-mathpnl’s home link. R package:wooldridge R Dataset:mathpnl

1844. meap00_01

name:rdataset-wooldridge-meap00_01 reference:rdataset-wooldridge-meap00_01’s home link. R package:wooldridge R Dataset:meap00_01

1845. meap01

name:rdataset-wooldridge-meap01 reference:rdataset-wooldridge-meap01’s home link. R package:wooldridge R Dataset:meap01

1846. meap93

name:rdataset-wooldridge-meap93 reference:rdataset-wooldridge-meap93’s home link. R package:wooldridge R Dataset:meap93

1847. meapsingle

name:rdataset-wooldridge-meapsingle reference:rdataset-wooldridge-meapsingle’s home link. R package:wooldridge R Dataset:meapsingle

1848. minwage

name:rdataset-wooldridge-minwage reference:rdataset-wooldridge-minwage’s home link. R package:wooldridge R Dataset:minwage

1849. mlb1

name:rdataset-wooldridge-mlb1 reference:rdataset-wooldridge-mlb1’s home link. R package:wooldridge R Dataset:mlb1

1850. mroz

name:rdataset-wooldridge-mroz reference:rdataset-wooldridge-mroz’s home link. R package:wooldridge R Dataset:mroz

1851. murder

name:rdataset-wooldridge-murder reference:rdataset-wooldridge-murder’s home link. R package:wooldridge R Dataset:murder

1852. nbasal

name:rdataset-wooldridge-nbasal reference:rdataset-wooldridge-nbasal’s home link. R package:wooldridge R Dataset:nbasal

1853. ncaa_rpi

name:rdataset-wooldridge-ncaa_rpi reference:rdataset-wooldridge-ncaa_rpi’s home link. R package:wooldridge R Dataset:ncaa_rpi

1854. nyse

name:rdataset-wooldridge-nyse reference:rdataset-wooldridge-nyse’s home link. R package:wooldridge R Dataset:nyse

1855. okun

name:rdataset-wooldridge-okun reference:rdataset-wooldridge-okun’s home link. R package:wooldridge R Dataset:okun

1856. openness

name:rdataset-wooldridge-openness reference:rdataset-wooldridge-openness’s home link. R package:wooldridge R Dataset:openness

1857. pension

name:rdataset-wooldridge-pension reference:rdataset-wooldridge-pension’s home link. R package:wooldridge R Dataset:pension

1858. phillips

name:rdataset-wooldridge-phillips reference:rdataset-wooldridge-phillips’s home link. R package:wooldridge R Dataset:phillips

1859. pntsprd

name:rdataset-wooldridge-pntsprd reference:rdataset-wooldridge-pntsprd’s home link. R package:wooldridge R Dataset:pntsprd

1860. prison

name:rdataset-wooldridge-prison reference:rdataset-wooldridge-prison’s home link. R package:wooldridge R Dataset:prison

1861. prminwge

name:rdataset-wooldridge-prminwge reference:rdataset-wooldridge-prminwge’s home link. R package:wooldridge R Dataset:prminwge

1862. rdchem

name:rdataset-wooldridge-rdchem reference:rdataset-wooldridge-rdchem’s home link. R package:wooldridge R Dataset:rdchem

1863. rdtelec

name:rdataset-wooldridge-rdtelec reference:rdataset-wooldridge-rdtelec’s home link. R package:wooldridge R Dataset:rdtelec

1864. recid

name:rdataset-wooldridge-recid reference:rdataset-wooldridge-recid’s home link. R package:wooldridge R Dataset:recid

1865. rental

name:rdataset-wooldridge-rental reference:rdataset-wooldridge-rental’s home link. R package:wooldridge R Dataset:rental

1866. return

name:rdataset-wooldridge-return reference:rdataset-wooldridge-return’s home link. R package:wooldridge R Dataset:return

1867. saving

name:rdataset-wooldridge-saving reference:rdataset-wooldridge-saving’s home link. R package:wooldridge R Dataset:saving

1868. school93_98

name:rdataset-wooldridge-school93_98 reference:rdataset-wooldridge-school93_98’s home link. R package:wooldridge R Dataset:school93_98

1869. sleep75

name:rdataset-wooldridge-sleep75 reference:rdataset-wooldridge-sleep75’s home link. R package:wooldridge R Dataset:sleep75

1870. slp75_81

name:rdataset-wooldridge-slp75_81 reference:rdataset-wooldridge-slp75_81’s home link. R package:wooldridge R Dataset:slp75_81

1871. smoke

name:rdataset-wooldridge-smoke reference:rdataset-wooldridge-smoke’s home link. R package:wooldridge R Dataset:smoke

1872. traffic1

name:rdataset-wooldridge-traffic1 reference:rdataset-wooldridge-traffic1’s home link. R package:wooldridge R Dataset:traffic1

1873. traffic2

name:rdataset-wooldridge-traffic2 reference:rdataset-wooldridge-traffic2’s home link. R package:wooldridge R Dataset:traffic2

1874. twoyear

name:rdataset-wooldridge-twoyear reference:rdataset-wooldridge-twoyear’s home link. R package:wooldridge R Dataset:twoyear

1875. volat

name:rdataset-wooldridge-volat reference:rdataset-wooldridge-volat’s home link. R package:wooldridge R Dataset:volat

1876. vote1

name:rdataset-wooldridge-vote1 reference:rdataset-wooldridge-vote1’s home link. R package:wooldridge R Dataset:vote1

1877. vote2

name:rdataset-wooldridge-vote2 reference:rdataset-wooldridge-vote2’s home link. R package:wooldridge R Dataset:vote2

1878. voucher

name:rdataset-wooldridge-voucher reference:rdataset-wooldridge-voucher’s home link. R package:wooldridge R Dataset:voucher

1879. wage1

name:rdataset-wooldridge-wage1 reference:rdataset-wooldridge-wage1’s home link. R package:wooldridge R Dataset:wage1

1880. wage2

name:rdataset-wooldridge-wage2 reference:rdataset-wooldridge-wage2’s home link. R package:wooldridge R Dataset:wage2

1881. wagepan

name:rdataset-wooldridge-wagepan reference:rdataset-wooldridge-wagepan’s home link. R package:wooldridge R Dataset:wagepan

1882. wageprc

name:rdataset-wooldridge-wageprc reference:rdataset-wooldridge-wageprc’s home link. R package:wooldridge R Dataset:wageprc

1883. wine

name:rdataset-wooldridge-wine reference:rdataset-wooldridge-wine’s home link. R package:wooldridge R Dataset:wine

Using the Socrata API

This tutorial explains the usage of the Socrata API in Data Retriever. It includes both the CLI (Command Line Interface) commands as well as the Python interface for the same.

Note

Currently Data Retriever only supports tabular Socrata datasets (tabular Socrata datasets which are of type map are not supported).

Command Line Interface

Listing the Socrata Datasets

The retriever ls -s command displays the Socrata datasets which contain the provided keywords in their title.

$ retriever ls -h (gives listing options)

usage: retriever ls [-h] [-l L [L ...]] [-k K [K ...]] [-v V [V ...]]
                [-s S [S ...]]

optional arguments:
  -h, --help    show this help message and exit
  -l L [L ...]  search datasets with specific license(s)
  -k K [K ...]  search datasets with keyword(s)
  -v V [V ...]  verbose list of specified dataset(s)
  -s S [S ...]  search socrata datasets with name(s)

Example

This example will list the names of the socrata datasets which contain the word fishing.

$ retriever ls -s fishing

Autocomplete suggestions : Total 34 results

[?] Select the dataset name: Recommended Fishing Rivers And Streams
 > Recommended Fishing Rivers And Streams
   Recommended Fishing Rivers And Streams API
   Iowa Fishing Report
   Recommended Fishing Rivers, Streams, Lakes and Ponds Map
   Public Fishing Rights Parking Areas Map
   Fishing Atlas
   Cook County - Fishing Lakes
   [ARCHIVED] Fishing License Sellers
   Public Fishing Rights Parking Areas
   Recommended Fishing Lakes and Ponds Map
   Recommended Fishing Lakes and Ponds
   Delaware Fishing Licenses and Trout Stamps
   Cook County - Fishing Lakes - KML

Here the user is prompted to select a dataset name. After selecting a dataset, the command returns some information related to the dataset selected.

Let’s select the Public Fishing Rights Parking Areas dataset, after pressing Enter, the command returns some information regarding the dataset selected.

Autocomplete suggestions : Total 34 results

[?] Select the dataset name: Public Fishing Rights Parking Areas
   Iowa Fishing Report
   Recommended Fishing Rivers, Streams, Lakes and Ponds Map
   Fishing Atlas
   Public Fishing Rights Parking Areas Map
   [ARCHIVED] Fishing License Sellers
   Cook County - Fishing Lakes
 > Public Fishing Rights Parking Areas
   Recommended Fishing Lakes and Ponds Map
   Recommended Fishing Lakes and Ponds
   Delaware Fishing Licenses and Trout Stamps
   Cook County - Fishing Lakes - KML
   General Fishing and Salmon Licence Sales
   Hunting and Fishing License Sellers

Dataset Information of Public Fishing Rights Parking Areas: Total 1 results

1. Public Fishing Rights Parking Areas
  ID : 9vef-6whi
  Type : {'dataset': 'tabular'}
  Description : The New York State Department of Environmental Con...
  Domain : data.ny.gov
  Link : https://data.ny.gov/Recreation/Public-Fishing-Rights-Parking-Areas/9vef-6whi

Downloading the Socrata Datasets

The retriever download socrata-<socrata id> command downloads the Socrata dataset which matches the provided socrata id.

Example

From the example in Listing the Socrata Datasets section, we selected the Public Fishing Rights Parking Areas dataset. Since the dataset is of type tabular, we can download it. The information received in the previous example contains the socrata id. We use this socrata id to download the dataset.

$ retriever download socrata-9vef-6whi

=> Installing socrata-9vef-6whi
Downloading 9vef-6whi.csv: 10.0B [00:03, 2.90B/s]
Done!

The downloaded raw data files are stored in the raw_data directory in the ~/.retriever directory.

Installing the Socrata Datasets

The retriever install <engine> socrata-<socrata id> command downloads the raw data, creates the script for it and then installs the Socrata dataset which matches the provided socrata id into the provided engine.

Example

From the example in Listing the Socrata Datasets section, we selected the Public Fishing Rights Parking Areas dataset. Since the dataset is of type tabular, we can install it. The information received in that section contains the socrata id. We use this socrata id to install the dataset.

$ retriever install postgres socrata-9vef-6whi

=> Installing socrata-9vef-6whi
Downloading 9vef-6whi.csv: 10.0B [00:03, 2.69B/s]
Processing... 9vef-6whi.csv
Successfully wrote scripts to /home/user/.retriever/socrata-scripts/9vef_6whi.csv.json
Updating script name to socrata-9vef-6whi.json
Updating the contents of script socrata-9vef-6whi
Successfully updated socrata_9vef_6whi.json
Creating database socrata_9vef_6whi...

Bulk insert on ..  socrata_9vef_6whi.socrata_9vef_6whi
Done!

The script created for the Socrata dataset is stored in the socrata-scripts directory in the ~/.retriever directory.

Python Interface in Data Retriever

Searching Socrata Datasets

The function socrata_autocomplete_search takes a list of strings as input and returns a list of strings which are the autocompleted names.

>>> import retriever as rt
>>> names = rt.socrata_autocomplete_search(['clinic', '2015', '2016'])
>>> for name in names:
...     print(name)
...
2016 & 2015 Clinic Quality Comparisons for Clinics with Five or More Service Providers
2015 - 2016 Clinical Quality Comparison (>=5 Providers) by Geography
2016 & 2015 Clinic Quality Comparisons for Clinics with Fewer than Five Service Providers

Socrata Dataset Info by Dataset Name

The input argument for the function socrata_dataset_info should be a string (valid dataset name returned by socrata_autocomplete_search). It returns a list of dicts, because there are multiple datasets on socrata with same name (e.g. Building Permits).

>>> import retriever as rt
>>> resource = rt.socrata_dataset_info('2016 & 2015 Clinic Quality Comparisons for Clinics with Five or More Service Providers')
>>> from pprint import pprint
>>> pprint(resource)
[{'description': 'This data set includes comparative information for clinics '
                 'with five or more physicians for medical claims in 2015 - '
                 '2016. \r\n'
                 '\r\n'
                 'This data set was calculated by the Utah Department of '
                 'Health, Office of Healthcare Statistics (OHCS) using Utah’s '
                 'All Payer Claims Database (APCD).',
  'domain': 'opendata.utah.gov',
  'id': '35s3-nmpm',
  'link': 'https://opendata.utah.gov/Health/2016-2015-Clinic-Quality-Comparisons-for-Clinics-w/35s3-nmpm',
  'name': '2016 & 2015 Clinic Quality Comparisons for Clinics with Five or '
          'More Service Providers',
  'type': {'dataset': 'tabular'}}]

Finding Socrata Dataset by Socrata ID

The input argument of the function find_socrata_dataset_by_id should be the four-by-four socrata dataset identifier (e.g. 35s3-nmpm). The function returns a dict which contains metadata about the dataset.

>>> import retriever as rt
>>> from pprint import pprint
>>> resource = rt.find_socrata_dataset_by_id('35s3-nmpm')
>>> pprint(resource)
{'datatype': 'tabular',
 'description': 'This data set includes comparative information for clinics '
                'with five or more physicians for medical claims in 2015 - '
                '2016. \r\n'
                '\r\n'
                'This data set was calculated by the Utah Department of '
                'Health, Office of Healthcare Statistics (OHCS) using Utah’s '
                'All Payer Claims Database (APCD).',
 'domain': 'opendata.utah.gov',
 'homepage': 'https://opendata.utah.gov/Health/2016-2015-Clinic-Quality-Comparisons-for-Clinics-w/35s3-nmpm',
 'id': '35s3-nmpm',
 'keywords': ['socrata'],
 'name': '2016 & 2015 Clinic Quality Comparisons for Clinics with Five or More '
         'Service Providers'}

Downloading a Socrata Dataset

import retriever as rt
rt.download('socrata-35s3-nmpm')

Installing a Socrata Dataset

import retriever as rt
rt.install_postgres('socrata-35s3-nmpm')

Note

For downloading or installing the Socrata Datasets, the dataset should follow the syntax given. The dataset name should be socrata-<socrata id>. The socrata id should be the four-by-four socrata dataset identifier (e.g. 35s3-nmpm).

Example:

• Correct: socrata-35s3-nmpm
• Incorrect: socrata35s3-nmpm, socrata35s3nmpm

Using the Rdatasets API

This tutorial explains the usage of the Rdatasets API in Data Retriever. It includes both the CLI (Command Line Interface) commands as well as the Python interface for the same.

Command Line Interface

Listing the Rdatasets

The retriever ls rdataset command displays the Rdatasets.

$ retriever ls rdataset -h (gives listing options)

usage: retriever ls rdataset [-h] [-p P [P ...]] all

positional arguments:
    all           display all the packages present in rdatasets

optional arguments:
    -h, --help    show this help message and exit
    -p P [P ...]  display a list of all rdatasets present in the package(s)

Examples

This example will display all the Rdatasets present with their package name, dataset name and script name

$ retriever ls rdataset

List of all available Rdatasets

Package: aer              Dataset: affairs                   Script Name: rdataset-aer-affairs
Package: aer              Dataset: argentinacpi              Script Name: rdataset-aer-argentinacpi
Package: aer              Dataset: bankwages                 Script Name: rdataset-aer-bankwages
...
Package: vcd              Dataset: vonbort                   Script Name: rdataset-vcd-vonbort
Package: vcd              Dataset: weldondice                Script Name: rdataset-vcd-weldondice
Package: vcd              Dataset: womenqueue                Script Name: rdataset-vcd-womenqueue

This example will display all the Rdatasets present in the packages vcd and aer

$ retriever ls rdataset -p vcd aer

List of all available Rdatasets in packages: ['vcd', 'aer']
Package: vcd              Dataset: arthritis                 Script Name: rdataset-vcd-arthritis
Package: vcd              Dataset: baseball                  Script Name: rdataset-vcd-baseball
Package: vcd              Dataset: brokenmarriage            Script Name: rdataset-vcd-brokenmarriage
...
Package: aer              Dataset: affairs                   Script Name: rdataset-aer-affairs
Package: aer              Dataset: argentinacpi              Script Name: rdataset-aer-argentinacpi
Package: aer              Dataset: bankwages                 Script Name: rdataset-aer-bankwages
...

This example will display all the Rdatasets present in the package vcd

$ retriever ls rdataset -p vcd

List of all available Rdatasets in packages: ['vcd', 'aer']
Package: vcd              Dataset: arthritis                 Script Name: rdataset-vcd-arthritis
Package: vcd              Dataset: baseball                  Script Name: rdataset-vcd-baseball
Package: vcd              Dataset: brokenmarriage            Script Name: rdataset-vcd-brokenmarriage
...

This example will display all the packages present in rdatasets

$ retriever ls rdataset all

List of all the packages present in Rdatasets

aer         cluster   dragracer  fpp2           gt        islr     mass        multgee         plyr      robustbase  stevedata
asaur       count     drc        gap            histdata  kmsurv   mediation   nycflights13    pscl      rpart       survival
boot        daag      ecdat      geepack        hlmdiag   lattice  mi          openintro       psych     sandwich    texmex
cardata     datasets  evir       ggplot2        hsaur     lme4     mosaicdata  palmerpenguins  quantreg  sem         tidyr
causaldata  dplyr     forecast   ggplot2movies  hwde      lmec     mstate      plm             reshape2  stat2data   vcd

Downloading the Rdatasets

The retriever download rdataset-<package>-<dataset> command downloads the Rdataset dataset which exists in the package package. You can also copy the script name from the output of retriever ls rdataset.

Example

This example downloads the rdataset-vcd-bundesliga dataset.

$ retriever download rdataset-vcd-bundesliga

=> Installing rdataset-vcd-bundesliga
Downloading Bundesliga.csv: 60.0B [00:00, 117B/s]
Done!

The downloaded raw data files are stored in the raw_data directory in the ~/.retriever directory.

Installing the Rdatasets

The retriever install <engine> rdataset-<package>-<dataset> command downloads the raw data, creates the script for it and then installs the Rdataset dataset present in the package package into the provided engine.

Example

This example install the rdataset-aer-usmoney dataset into the postgres engine.

$ retriever install postgres rdataset-aer-usmoney

=> Installing rdataset-aer-usmoney
Downloading USMoney.csv: 1.00B [00:00, 2.52B/s]
Processing... USMoney.csv
Successfully wrote scripts to /home/user/.retriever/rdataset-scripts/usmoney.csv.json
Updating script name to rdataset-aer-usmoney.json
Updating the contents of script rdataset-aer-usmoney
Successfully updated rdataset_aer_usmoney.json
Updated the script rdataset-aer-usmoney
Creating database rdataset_aer_usmoney...

Installing rdataset_aer_usmoney.usmoney
Progress: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 136/136 [00:00<00:00, 2225.09rows/s]
Done!

The script created for the Rdataset is stored in the rdataset-scripts directory in the ~/.retriever directory.

Python Interface in Data Retriever

Updating Rdatasets Catalog

The function update_rdataset_catalog creates/updates the datasets_url.json in the ~/.retriever/rdataset-scripts directory, which contains the information about all the Rdatasets.

>>> import retriever as rt
>>> rt.update_rdataset_catalog()

Note

The update_rdataset_catalog function has a default argument test which is set to False. If test is set to True, then the contents of the datasets_url.json file would be returned as a dict.

Listing Rdatasets

The function display_all_rdataset_names prints the package, dataset name and the script name for the Rdatasets present in the package(s) requested. If no package is specified, it prints all the rdatasets, and if all is passed as the function argument then all the package names are displayed.

Note

The function argument package_name takes a list as an input when you want to display rdatasets based on the packages. If you want to display all packages names, set package_name argument to all (refer to the example below).

>>> import retriever as rt
>>>
>>> # Display all Rdatasets
>>> rt.display_all_rdataset_names()
List of all available Rdatasets

Package: aer              Dataset: affairs                   Script Name: rdataset-aer-affairs
Package: aer              Dataset: argentinacpi              Script Name: rdataset-aer-argentinacpi
Package: aer              Dataset: bankwages                 Script Name: rdataset-aer-bankwages
...
Package: vcd              Dataset: vonbort                   Script Name: rdataset-vcd-vonbort
Package: vcd              Dataset: weldondice                Script Name: rdataset-vcd-weldondice
Package: vcd              Dataset: womenqueue                Script Name: rdataset-vcd-womenqueue
>>>
>>> # Display all the Rdatasets present in packages 'aer' and 'drc'
>>> rt.display_all_rdataset_names(['aer', 'drc'])
List of all available Rdatasets in packages: ['aer', 'drc']
Package: aer              Dataset: affairs                   Script Name: rdataset-aer-affairs
Package: aer              Dataset: argentinacpi              Script Name: rdataset-aer-argentinacpi
Package: aer              Dataset: bankwages                 Script Name: rdataset-aer-bankwages
...
Package: drc              Dataset: spinach                   Script Name: rdataset-drc-spinach
Package: drc              Dataset: terbuthylazin             Script Name: rdataset-drc-terbuthylazin
Package: drc              Dataset: vinclozolin               Script Name: rdataset-drc-vinclozolin
>>>
>>> # Display all the packages in Rdatasets
>>> rt.display_all_rdataset_names('all')
List of all the packages present in Rdatasets

aer         cluster   dragracer  fpp2           gt        islr     mass        multgee         plyr      robustbase  stevedata
asaur       count     drc        gap            histdata  kmsurv   mediation   nycflights13    pscl      rpart       survival
boot        daag      ecdat      geepack        hlmdiag   lattice  mi          openintro       psych     sandwich    texmex
cardata     datasets  evir       ggplot2        hsaur     lme4     mosaicdata  palmerpenguins  quantreg  sem         tidyr
causaldata  dplyr     forecast   ggplot2movies  hwde      lmec     mstate      plm             reshape2  stat2data   vcd

Downloading a Rdataset

>>> import retriever as rt
>>> rt.download('rdataset-drc-earthworms')

Installing a Rdataset

>>> import retriever as rt
>>> rt.install_postgres('rdataset-mass-galaxies')

Note

For downloading or installing the Rdatasets, the script name should follow the syntax given below. The script name should be rdataset-<package name>-<dataset name>. The package name and dataset name should be valid.

Example:

• Correct: rdataset-drc-earthworms
• Incorrect: rdataset-drcearthworms, rdatasetdrcearthworms

Developer’s guide

1. Quickstart by forking the main repository https://github.com/weecology/retriever

2. Clone your copy of the repository

   • Using https git clone https://github.com/henrykironde/retriever.git
   • Using ssh git clone git@github.com:henrykironde/retriever.git

3. Link or point your cloned copy to the main repository. (I always name it upstream)

   • git remote add upstream https://github.com/weecology/retriever.git

5. Check/confirm your settings using git remote -v

origin      git@github.com:henrykironde/retriever.git (fetch)
origin      git@github.com:henrykironde/retriever.git (push)
upstream    https://github.com/weecology/retriever.git (fetch)
upstream    https://github.com/weecology/retriever.git (push)

6. Install the package from the main directory. use -U or –upgrade to upgrade or overwrite any previously installed versions.

pip install . -U

7. Check if the package was installed

retriever ls
retriever -v

8. Run sample test on CSV engine only, with the option -k

pip install pytest
pytest -k "CSV" -v

Required Modules

You will need Python 3.6.8+ Make sure the required modules are installed: Pip install -r requirements.txt

Developers need to install these extra packages.

pip install codecov
pip install pytest-cov
pip install pytest-xdist
pip install pytest
pip install yapf
pip install pylint
pip install flake8
Pip install pypyodbc # For only Windows(MS Access)

Setting up servers

You need to install all the database infrastructures to enable local testing.

PostgresSQL MySQL SQLite MSAccess (For only Windows, MS Access)

After installation, configure passwordless access to MySQL and PostgresSQL Servers

Passwordless configuration

To avoid supplying the passwords when using the tool, use the config files .pgpass`(`pgpass.conf for Microsoft Windows) for Postgres and .my.cnf for MySQL.

Create if not exists, and add/append the configuration details as below. PostgresSQL conf file ~/.pgpass file.

For more information regarding Passwordless configuration you can visit PostgreSQL Password File and MySQL Password File

localhost:*:*:postgres:Password12!

Postgress:

(Linux / Macos):- A .pgpass file in your HOME directory(~)

(WINDOWS 10-) - A pgpass.conf in your HOME directory(~)

(WINDOWS 10+):- Entering %APPDATA% will take you to C:/Users/username/AppData/Roaming.

In this directory create a new subdirectory named postgresql. Then create the pgpass.conf file inside it. On Microsoft Windows, it is assumed that the file is stored in a secure directory, hence no special permissions setting is needed.

Make sure you set the file permissions to 600

# Linux / Macos
chmod 600 ~/.pgpass
chmod 600 ~/.my.cnf

For most of the recent versions of Postgress server 10+, you need to find pg_hba.conf. This file is located in the installed Postgres directory. One way to find the location of the file pg_hba.conf is using psql -t -P format=unaligned -c 'show hba_file'; To allow passwordless login to Postgres, change peer to trust in pg_hba.conf file.

# Database administrative login by Unix domain socket
local   all             postgres                                trust

Run commands in terminal to create user

PostgreSQL
----------
psql -c "CREATE USER postgres WITH PASSWORD 'Password12!'"
psql -c 'CREATE DATABASE testdb_retriever'
psql -c 'GRANT ALL PRIVILEGES ON DATABASE testdb_retriever to postgres'

Restart the server and test Postgress passwordless setup using retriever without providing the password

retriever install postgres iris

MySQL: Create if not exists .my.cnf in your HOME directory(~). Add the configuration info to the MySQL conf file ~.my.cnf file.

[client]
user="travis"
password="Password12!"
host="mysqldb"
port="3306"

Run commands in terminal to create user

 MySQL
 -----
 mysql -e "CREATE USER 'travis'@'localhost';" -uroot
 mysql -e "GRANT ALL PRIVILEGES ON *.* TO 'travis'@'localhost';" -uroot
 mysql -e "GRANT FILE ON *.* TO 'travis'@'localhost';" -uroot

Restart the server and test MySQL passwordless setup using retriever without providing the password

retriever install mysql iris

Testing

Before running the tests make sure Postgis is set up Spatial database setup.

Follow these instructions to run a complete set of tests for any branch Clone the branch you want to test.

Two ways of installing the program using the setup tools.

we can either install from source as

pip install . --upgrade or python setup.py install

or install in development mode.

python setup.py develop

For more about installing refer to the python setuptools documentation.

you can also install from Git.

# Local repository
pip install git+file:///path/to/your/git/repo #  test a PIP package located in a local git repository
pip install git+file:///path/to/your/git/repo@branch  # checkout a specific branch by adding @branch_name at the end

# Remote GitHub repository
pip install git+git://github.com/myuser/myproject  #  package from a GitHub repository
pip install git+git://github.com/myuser/myproject@my_branch # github repository Specific branch

Running tests locally

Services Used

Read The Docs, codecov, AppVeyor

From the source top-level directory, Use Pytest as examples below

$   py.test -v # All tests
$   py.test -v -k"csv" # Specific test with expression csv
$   py.test ./test/test_retriever.py # Specific file

In case py.test requests for Password (even after Passwordless configuration), change the owner and group permissions for the config files ~/.pgpass, ~/.my.cnf

Style Guide for Python Code

Use yapf -d --recursive retriever/ --style=.style.yapf to check style.

Use yapf -i --recursive retriever/ --style=.style.yapf refactor style

Continuous Integration

The main GitHub repository runs the test on both the GitHub Actions (Linux) and AppVeyor (Windows) continuous-integration platforms.

Pull requests submitted to the repository will automatically be tested using these systems and results reported in the checks section of the pull request page.

Create Release

Start

1. Run the tests. Seriously, do it now.

2. Update CHANGES.md with major updates since the last release

3. Run python version.py (this will update version.txt)

4. In the main branch update the version number and create a tag, run bumpversion release

5. Push the release commit and the tag

6. After the release, update the version to dev, run bumpversion patch

   git push upstream main
   git push upstream --tags
   

Pypi

You will need to create an API key on PyPI and store it in ~/.pypirc to upload to PyPI.

1. sudo python setup.py sdist bdist_wheel
2. sudo python -m twine upload -r pypi dist/*

Cleanup

1. Bump the version numbers as needed. The version number is located in the setup.py, retriever_installer.iss, version.txt and retriever/_version.py

Mac OSX Build

Building the Retriever on OSX.

Python binaries

This build will allow you to successfully build the Mac App for distribution to other systems.

1. Install the Python 3 Installer (or Python 2 if you have a specific reason for doing so) from the Python download site.
2. Use pip to install any desired optional dependencies pip install pymysql psycopg2-binary pyinstaller pytest You will need all of these dependencies, for example pyinstaller, if you want to build the Mac App for distribution

Homebrew

Homebrew works great if you just want to install the Retriever from source on your machine, but at least based on this recipe it does not support the distribution of the Mac App to other versions of OS X (i.e., if you build the App on OS X 10.9 it will only run on 10.9)

1. Install Homebrew ruby -e "$(curl -fsSL https://raw.github.com/mxcl/homebrew/go)"
2. Install Xcode
3. Install Python brew install python
4. Install the Xcode command-line tools xcode-select --install
5. Make brew’s Python the default echo export PATH='usr/local/bin:$PATH' >> ~/.bash_profile
6. Install xlrd via pip pip install xlrd. No sudo is necessary since we’re using brew.
7. Clone the Retriever git clone git@github.com:weecology/retriever.git
8. Switch directories cd retriever
9. Standard install pip install . --upgrade

If you also want to install the dependencies for MySQL and PostgreSQL this can be done using a combination of homebrew and pip.

1. brew install mysql
2. Follow the instructions from brew for starting MySQL
3. brew install postgresql
4. Follow the instructions from brew for starting Postgres
5. sudo pip install pymysql MySQL-python psycopg2-binary

MySQL-python should be installed in addition to pymysql for building the .app file since pymysql is not currently working properly in the .app.

Conda

• This hasn’t been tested yet

Creating or Updating a Conda Release

To create or update a Conda Release, first fork the conda-forge retriever-feedstock repository.

Once forked, open a pull request to the retriever-feedstock repository. Your package will be tested on Windows, Mac, and Linux.

When your pull request is merged, the package will be rebuilt and become automatically available on conda-forge.

All branches in the conda-forge/retriever-feedstock are created and uploaded immediately, so PRs should be based on branches in forks. Branches in the main repository shall be used to build distinct package versions only.

For producing a uniquely identifiable distribution:

• If the version of a package is not being incremented, then the build/number can be added or increased.
• If the version of a package is being incremented, then remember to change the build/number back to 0.

Documentation

We are using Sphinx and Read the Docs. for the documentation. Sphinx uses reStructuredText as its markup language. Source Code documentation is automatically included after committing to the main. Other documentation (not source code) files are added as new reStructuredText in the docs folder

In case you want to change the organization of the Documentation, please refer to Sphinx

Update Documentation

The documentation is automatically updated for changes within modules. However, the documentation should be updated after the addition of new modules in the engines or lib directory. Change to the docs directory and create a temporary directory, i.e. source. Run

cd  docs
mkdir source
sphinx-apidoc -f  -o ./source /Users/../retriever/

The source is the destination folder for the source rst files. /Users/../retriever/ is the path to where the retriever source code is located. Copy the .rst files that you want to update to the docs directory, overwriting the old files. Make sure you check the changes and edit if necessary to ensure that only what is required is updated. Commit and push the new changes. Do not commit the temporary source directory.

Test Documentation locally

cd  docs  # go the docs directory
make html && python3 -m http.server --directory _build/html
# Makes the html files and hosts a HTTP server on localhost:8000 to view the documentation pages locally

Note

Do not commit the _build directory after making HTML.

Read The Docs configuration

Configure read the docs (advanced settings) so that the source is first installed then docs are built. This is already set up but could be changed if need be.

Collaborative Workflows with GitHub

First fork the Data Retriever repository. Then Clone your forked version with either HTTPS or SSH

# Clone with HTTPS
git clone https://github.com/[myusername]/retriever.git
# Clone with SSH
git clone git@github.com:[myusername]/retriever.git

This will update your .git/config to point to your repository copy of the Data Retriever as remote “origin”

[remote "origin"]
url = git@github.com:[myusername]/retriever.git
fetch = +refs/heads/*:refs/remotes/origin/*

Point to Weecology Data Retriever repository repo. This will enable you to update your main(origin) and you can then push to your origin main. In our case, we can call this upstream().

git remote add upstream https://github.com/weecology/retriever.git

This will update your .git/config to point to the Weecology Data Retriever repository.

[remote "upstream"]
url = https://github.com/weecology/retriever.git
fetch = +refs/heads/*:refs/remotes/upstream/*
# To fetch pull requests add
fetch = +refs/pull/*/head:refs/remotes/origin/pr/*

Fetch upstream main and create a branch to add the contributions to.

git fetch upstream
git checkout main
git reset --hard upstream main
git checkout -b [new-branch-to-fix-issue]

Submitting issues

Categorize the issues based on labels. For example (Bug, Dataset Bug, Important, Feature Request, etc..) Explain the issue explicitly with all details, giving examples and logs where applicable.

Commits

From your local branch of retriever, commit to your origin. Once tests have passed you can then make a pull request to the retriever main (upstream) For each commit, add the issue number at the end of the description with the tag fixes #[issue_number].

Example

Add version number to postgres.py to enable tracking

Skip a line and add more explanation if needed
fixes #3

Clean history

Make one commit for each issue. As you work on a particular issue, try adding all the commits into one general commit rather than several commits.

Use git commit --amend to add new changes to a branch.

Use -f flag to force pushing changes to the branch. git push -f origin [branch_name]

Spatial database setup

Supporting installation of spatial data into Postgres DBMS.

1. Install Postgres

For Mac the easiest way to get started with PostgreSQL is with Postgres.app.

For Debain and Ubuntu, install PostgresSQL and PostGis please ref to Postgres installation.

Otherwise you can try package installers for WINDOWS, MAC, Linux and MacOS from the main PostgreSQL download page

For simplicity, use .pgpass file(pgpass.conf file for Microsoft Windows) to avoid supplying the password every time as decribed in Passwordless configuration.

After installation, Make sure you have the paths to these tools added to your system’s PATHS.

Note: Older version of this raster2pgsql was a python script that you had to download and manually include in Postgres’s directory. Please consult an operating system expert for help on how to change or add the PATH variables.

For example, this could be a sample of paths exported on Mac:

#~/.bash_profile file, Postgres PATHS and tools .

2. Enable PostGIS extensions

If you have Postgres set up, enable PostGIS extensions. This is done by using either Postgres CLI or GUI(PgAdmin) and run the commands below.

For psql CLI

For GUI(PgAdmin)

For more details refer to the Postgis docs.

Note

PostGIS excluded the raster types and functions from the main extension as of version 3.x; A separate CREATE EXTENSION postgis_raster; is then needed to get raster support.

Versions 2.x have full raster support as part of the main extension environment, so CREATE EXTENSION postgis; is all that you need`

Contributor Code of Conduct

Our Pledge

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.

Our Standards

Examples of behavior that contributes to creating a positive environment include:

Using welcoming and inclusive language Being respectful of differing viewpoints and experiences Gracefully accepting constructive criticism Focusing on what is best for the community Showing empathy towards other community members Examples of unacceptable behavior by participants include:

The use of sexualized language or imagery and unwelcome sexual attention or advances Trolling, insulting/derogatory comments, and personal or political attacks Public or private harassment Publishing others’ private information, such as a physical or electronic address, without explicit permission Other conduct which could reasonably be considered inappropriate in a professional setting

Our Responsibilities

Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.

Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.

Scope

This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.

Enforcement

Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at ethan@weecology.org. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.

Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project’s leadership.

Attribution

This Code of Conduct is adapted from the Contributor Covenant, version 1.4.

Retriever API

retriever package

Subpackages

retriever.engines package

Submodules

retriever.engines.csvengine module

class retriever.engines.csvengine.engine

Bases: retriever.lib.engine.Engine

Engine instance for writing data to a CSV file.

abbreviation = 'csv'

auto_column_number = 0

create_db()

Override create_db since there is no database just a CSV file

create_table()

Create the table by creating an empty csv file

datatypes = {'auto': 'INTEGER', 'bigint': 'INTEGER', 'bool': 'INTEGER', 'char': 'TEXT', 'decimal': 'REAL', 'double': 'REAL', 'int': 'INTEGER'}

disconnect()

Close the last file in the dataset

disconnect_files()

Close each file after being written

execute(statement, commit=True)

Write a line to the output file

executemany(statement, values, commit=True)

Write a line to the output file

format_insert_value(value, datatype)

Formats a value for an insert statement

get_connection()

Gets the db connection.

insert_limit = 1000

insert_statement(values)

Returns a comma delimited row of values

name = 'CSV'

required_opts = [('table_name', 'Format of table name', '{db}_{table}.csv'), ('data_dir', 'Install directory', '.')]

table_exists(dbname, tablename)

Check to see if the data file currently exists

table_names = []

to_csv(sort=True, path=None, select_columns=None)

Export sorted version of CSV file

retriever.engines.download_only module

retriever.engines.download_only.dummy_method(self, *args, **kwargs)

Dummy method template to help with replacing Engine functions

class retriever.engines.download_only.engine

Bases: retriever.lib.engine.Engine

Engine instance for writing data to a CSV file.

abbreviation = 'download'

all_files = {}

auto_create_table(table, url=None, filename=None, pk=None, make=True)

Download the file if it doesn’t exist

create_db(*args, **kwargs)

Dummy method template to help with replacing Engine functions

create_table(*args, **kwargs)

Dummy method template to help with replacing Engine functions

final_cleanup()

Copies downloaded files to desired directory

find_file(filename)

Checks for the given file and adds it to the list of all files

get_connection()

Gets the db connection.

insert_data_from_file(*args, **kwargs)

Dummy method template to help with replacing Engine functions

insert_data_from_url(url)

Insert data from a web resource

name = 'Download Only'

register_files(filenames)

Identify a list of files to be moved by the download

When downloading archives with multiple files the engine needs to be informed of all of the file names so that it can move them.

required_opts = [('path', 'File path to copy data files', './'), ('sub_dir', 'Install directory', '')]

table_exists(dbname, tablename)

Checks if the file to be downloaded already exists

retriever.engines.jsonengine module

Engine for writing data to a JSON file

class retriever.engines.jsonengine.engine

Bases: retriever.lib.engine.Engine

Engine instance for writing data to a JSON file.

abbreviation = 'json'

auto_column_number = 0

create_db()

Override create_db since there is no database just a JSON file

create_table()

Create the table by creating an empty json file

datatypes = {'auto': 'INTEGER', 'bigint': 'INTEGER', 'bool': 'INTEGER', 'char': 'TEXT', 'decimal': 'REAL', 'double': 'REAL', 'int': 'INTEGER'}

disconnect()

Close out the JSON with a n]} and close the file.

Close all the file objects that have been created Re-write the files stripping off the last comma and then close with a n]}.

execute(statement, commit=True)

Write a line to the output file

executemany(statement, values, commit=True)

Write a line to the output file

format_insert_value(value, datatype)

Formats a value for an insert statement

get_connection()

Gets the db connection.

insert_limit = 1000

insert_statement(values)

Return SQL statement to insert a set of values.

name = 'JSON'

required_opts = [('table_name', 'Format of table name', '{db}_{table}.json'), ('data_dir', 'Install directory', '.')]

table_exists(dbname, tablename)

Check to see if the data file currently exists

table_names = []

to_csv(sort=True, path=None, select_columns=None)

Export table from json engine to CSV file

retriever.engines.msaccess module

class retriever.engines.msaccess.engine

Bases: retriever.lib.engine.Engine

Engine instance for Microsoft Access.

abbreviation = 'msaccess'

convert_data_type(datatype)

MS Access can’t handle complex Decimal types

create_db()

MS Access doesn’t create databases.

datatypes = {'auto': 'AUTOINCREMENT', 'bigint': 'INTEGER', 'bool': 'BIT', 'char': 'VARCHAR', 'decimal': 'NUMERIC', 'double': 'NUMERIC', 'int': 'INTEGER'}

drop_statement(object_type, object_name)

Returns a drop table or database SQL statement.

get_connection()

Gets the db connection.

insert_data_from_file(filename)

Perform a bulk insert.

insert_limit = 1000

instructions = 'Create a database in Microsoft Access, close Access.\nThen select your database file using this dialog.'

name = 'Microsoft Access'

placeholder = '?'

required_opts = [('file', 'Enter the filename of your Access database', 'access.mdb', 'Access databases (*.mdb, *.accdb)|*.mdb;*.accdb'), ('table_name', 'Format of table name', '[{db} {table}]'), ('data_dir', 'Install directory', '.')]

retriever.engines.mysql module

class retriever.engines.mysql.engine

Bases: retriever.lib.engine.Engine

Engine instance for MySQL.

abbreviation = 'mysql'

create_db_statement()

Return SQL statement to create a database.

datatypes = {'auto': 'INT(5) NOT NULL AUTO_INCREMENT', 'bigint': 'BIGINT', 'bool': 'BOOL', 'char': ('TEXT', 'VARCHAR'), 'decimal': 'DECIMAL', 'double': 'DOUBLE', 'int': 'INT'}

get_connection()

Get db connection. PyMySQL has changed the default encoding from latin1 to utf8mb4. https://github.com/PyMySQL/PyMySQL/pull/692/files For PyMySQL to work well on CI infrastructure, connect with the preferred charset

insert_data_from_file(filename)

Call MySQL “LOAD DATA LOCAL INFILE” statement to perform a bulk insert.

insert_limit = 1000

lookup_encoding()

Convert well known encoding to MySQL syntax MySQL has a unique way of representing the encoding. For example, latin-1 becomes latin1 in MySQL. Please update the encoding lookup table if the required encoding is not present.

max_int = 4294967295

name = 'MySQL'

placeholder = '%s'

required_opts = [('user', 'Enter your MySQL username', 'root'), ('password', 'Enter your password', ''), ('host', 'Enter your MySQL host', 'localhost'), ('port', 'Enter your MySQL port', 3306), ('database_name', 'Format of database name', '{db}'), ('table_name', 'Format of table name', '{db}.{table}')]

set_engine_encoding()

Set MySQL database encoding to match data encoding

table_exists(dbname, tablename)

Check to see if the given table exists.

retriever.engines.postgres module

class retriever.engines.postgres.engine

Bases: retriever.lib.engine.Engine

Engine instance for PostgreSQL.

abbreviation = 'postgres'

auto_create_table(table, url=None, filename=None, pk=None, make=True)

Create a table automatically.

Overwrites the main Engine class. Identifies the type of table to create. For a Raster or vector (Gis) dataset, create the table from the contents downloaded from the url or from the contents in the filename. Otherwise, use the Engine function for a tabular table.

create_db()

Create Engine database.

create_db_statement()

In PostgreSQL, the equivalent of a SQL database is a schema.

create_table()

Create a table and commit.

PostgreSQL needs to commit operations individually. Enable PostGis extensions if a script has a non tabular table.

datatypes = {'auto': 'serial', 'bigint': 'bigint', 'bool': 'boolean', 'char': 'varchar', 'decimal': 'decimal', 'double': 'double precision', 'int': 'integer'}

db_encoding = 'Latin1'

drop_statement(object_type, object_name)

In PostgreSQL, the equivalent of a SQL database is a schema.

format_insert_value(value, datatype)

Format value for an insert statement.

get_connection()

Gets the db connection.

Please update the encoding lookup table if the required encoding is not present.

insert_data_from_file(filename)

Use PostgreSQL’s “COPY FROM” statement to perform a bulk insert.

Current postgres engine bulk only supports comma delimiter

insert_limit = 1000

insert_raster(path=None, srid=4326)

Import Raster into Postgis Table Uses raster2pgsql -Y -M -d -I -s <SRID> <PATH> <SCHEMA>.<DBTABLE> | psql -d <DATABASE> The sql processed by raster2pgsql is run as psql -U postgres -d <gisdb> -f <elev>.sql -Y uses COPY to insert data, -M VACUUM table, -d Drops the table, recreates insert raster data

insert_statement(values)

Return SQL statement to insert a set of values.

insert_vector(path=None, srid=4326)

Import Vector into Postgis Table

– Enable PostGIS (includes raster) CREATE EXTENSION postgis;

– Enable Topology CREATE EXTENSION postgis_topology;

– fuzzy matching needed for Tiger CREATE EXTENSION fuzzystrmatch;

– Enable US Tiger Geocoder CREATE EXTENSION postgis_tiger_geocoder; Uses shp2pgsql -I -s <SRID> <PATH/TO/SHAPEFILE> <SCHEMA>.<DBTABLE> | psql -U postgres -d <DBNAME>>

The sql processed by shp2pgsql is run as psql -U postgres -d <DBNAME>> shp2pgsql -c -D -s 4269 -i -I

max_int = 2147483647

name = 'PostgreSQL'

placeholder = '%s'

required_opts = [('user', 'Enter your PostgreSQL username', 'postgres'), ('password', 'Enter your password', ''), ('host', 'Enter your PostgreSQL host', 'localhost'), ('port', 'Enter your PostgreSQL port', 5432), ('database', 'Enter your PostgreSQL database name', 'postgres'), ('database_name', 'Format of schema name', '{db}'), ('table_name', 'Format of table name', '{db}.{table}')]

spatial_support = True

supported_raster(path, ext=None)

Return the supported Gis raster files from the path

Update the extensions after testing if a given raster type is supported by raster2pgsql.

retriever.engines.sqlite module

class retriever.engines.sqlite.engine

Bases: retriever.lib.engine.Engine

Engine instance for SQLite.

abbreviation = 'sqlite'

create_db()

Don’t create database for SQLite

SQLite doesn’t create databases. Each database is a file and needs a separate connection. This overloads`create_db` to do nothing in this case.

datatypes = {'auto': ('INTEGER', 'AUTOINCREMENT'), 'bigint': 'INTEGER', 'bool': 'INTEGER', 'char': 'TEXT', 'decimal': 'REAL', 'double': 'REAL', 'int': 'INTEGER'}

fetch_tables(dataset, table_names)

Return sqlite dataset as list of pandas dataframe.

get_bulk_insert_statement()

Get insert statement for bulk inserts

This places ?’s instead of the actual values so that executemany() can operate as designed

get_connection()

Get db connection.

insert_data_from_file(filename)

Perform a high speed bulk insert

Checks to see if a given file can be bulk inserted, and if so loads it in chunks and inserts those chunks into the database using executemany.

insert_limit = 1000

name = 'SQLite'

placeholder = '?'

required_opts = [('file', 'Enter the filename of your SQLite database', 'sqlite.db'), ('table_name', 'Format of table name', '{db}_{table}'), ('data_dir', 'Install directory', '.')]

retriever.engines.xmlengine module

class retriever.engines.xmlengine.engine

Bases: retriever.lib.engine.Engine

Engine instance for writing data to a XML file.

abbreviation = 'xml'

auto_column_number = 0

create_db()

Override create_db since there is no database just an XML file.

create_table()

Create the table by creating an empty XML file.

datatypes = {'auto': 'INTEGER', 'bigint': 'INTEGER', 'bool': 'INTEGER', 'char': 'TEXT', 'decimal': 'REAL', 'double': 'REAL', 'int': 'INTEGER'}

disconnect()

Close out the xml files

Close all the file objects that have been created Re-write the files stripping off the last comma and then close with a closing tag)

execute(statement, commit=True)

Write a line to the output file.

executemany(statement, values, commit=True)

Write a line to the output file.

format_insert_value(value, datatype)

Format value for an insert statement.

get_connection()

Get db connection.

insert_limit = 1000

insert_statement(values)

Create the insert statement.

Wrap each data value with column values(key) using _format_single_row <key> value </key>.

name = 'XML'

required_opts = [('table_name', 'Format of table name', '{db}_{table}.xml'), ('data_dir', 'Install directory', '.')]

table_names = []

to_csv(sort=True, path=None, select_columns=None)

Export table from xml engine to CSV file.

retriever.engines.xmlengine.format_single_row(keys, line_data)

Create an xml string from the keys and line_data values.

retriever.lib package

Submodules

retriever.lib.cleanup module

class retriever.lib.cleanup.Cleanup(function=<function no_cleanup>, **kwargs)

Bases: object

This class represents a custom cleanup function and a dictionary of arguments to be passed to that function.

retriever.lib.cleanup.correct_invalid_value(value, args)

This cleanup function replaces missing value indicators with None.

retriever.lib.cleanup.floatable(value)

Check if a value can be converted to a float

retriever.lib.cleanup.no_cleanup(value, args)

Default cleanup function, returns the unchanged value.

retriever.lib.create_scripts module

Module to auto create scripts from source

class retriever.lib.create_scripts.RasterPk(**kwargs)

Bases: retriever.lib.create_scripts.TabularPk

Raster package class

create_raster_resources(file_path)

Get resource information from raster file

get_resources(file_path, driver_name=None, skip_lines=None, encoding=None)

Get raster resources

get_source(file_path, driver=None)

Read raster data source

multi_formats = ['hdf']

pk_formats = ['gif', 'img', 'bil', 'jpg', 'tif', 'tiff', 'hdf', 'l1b', '.gif', '.img', '.bil', '.jpg', '.tif', '.tiff', '.hdf', '.l1b']

set_global(src_ds)

Set raster specific properties

class retriever.lib.create_scripts.TabularPk(name='fill', title='fill', description='fill', citation='fill', licenses=[], keywords=[], archived='fill or remove this field if not archived', homepage='fill', version='1.0.0', resources=[], retriever='True', retriever_minimum_version='2.1.0', **kwargs)

Bases: object

Main Tabular data package

create_tabular_resources(file, skip_lines, encoding)

Create resources for tabular scripts

get_resources(file_path, driver_name=None, skip_lines=None, encoding='utf-8')

Get resource values from tabular data source

class retriever.lib.create_scripts.VectorPk(**kwargs)

Bases: retriever.lib.create_scripts.TabularPk

Vector package class

create_vector_resources(path, driver_name)

Create vector data resources

get_resources(file_path, driver_name=None, skip_lines=None, encoding=None)

Get resource values from tabular data source

get_source(source, driver_name=None)

Open a data source

pk_formats = ['.shp', 'shp']

set_globals(da_layer)

Set vector values

retriever.lib.create_scripts.clean_table_name(table_name)

Remove and replace chars . and ‘-’ with ‘_’

retriever.lib.create_scripts.create_package(path, data_type, file_flag, out_path=None, skip_lines=None, encoding='utf-8')

Creates package for a path

path: string path to files to be processed data_type: string data type of the files to be processed file_flag: boolean for whether the files are processed as files or directories out_path: string path to write scripts out to skip_lines: int number of lines to skip as a list encoding: encoding of source

retriever.lib.create_scripts.create_raster_datapackage(pk_type, path, file_flag, out_path)

Creates raster package for a path

retriever.lib.create_scripts.create_script_dict(pk_type, path, file, skip_lines, encoding)

Create a script dict or skips file if resources cannot be made

retriever.lib.create_scripts.create_tabular_datapackage(pk_type, path, file_flag, out_path, skip_lines, encoding)

Creates tabular package for a path

retriever.lib.create_scripts.create_vector_datapackage(pk_type, path, file_flag, out_path)

Creates vector package for a path

retriever.lib.create_scripts.get_directory(path)

Returns absolute directory path for a path.

retriever.lib.create_scripts.process_dirs(pk_type, sub_dirs_path, out_path, skip_lines, encoding)

Creates a script for each directory.

retriever.lib.create_scripts.process_singles(pk_type, single_files_path, out_path, skip_lines, encoding)

Creates a script for each file

If the filepath is a file, creates a single script for that file. If the filepath is a directory, creates a single script for each file in the directory.

retriever.lib.create_scripts.process_source(pk_type, path, file_flag, out_path, skip_lines=None, encoding='utf-8')

Process source file or source directory

retriever.lib.create_scripts.write_out_scripts(script_dict, path, out_path)

Writes scripts out to a given path

retriever.lib.datapackage module

retriever.lib.datapackage.clean_input(prompt='', split_char='', ignore_empty=False, dtype=None)

Clean the user-input from the CLI before adding it.

retriever.lib.datapackage.is_empty(val)

Check if a variable is an empty string or an empty list.

retriever.lib.datasets module

retriever.lib.datasets.dataset_licenses()

Return set with all available licenses.

retriever.lib.datasets.dataset_names()

Return list of all available dataset names.

retriever.lib.datasets.dataset_verbose_list(script_names: list)

Returns the verbose list of the specified dataset(s)

retriever.lib.datasets.datasets(keywords=None, licenses=None)

Search all datasets by keywords and licenses.

retriever.lib.datasets.license(dataset)

Get the license for a dataset.

retriever.lib.defaults module

retriever.lib.download module

retriever.lib.download.download(dataset, path='./', quiet=False, sub_dir='', debug=False, use_cache=True)

Download scripts for retriever.

retriever.lib.dummy module

Dummy connection classes for connectionless engine instances

This module contains dummy classes required for non-db based children of the Engine class.

class retriever.lib.dummy.DummyConnection

Bases: object

Dummy connection class

close()

Dummy close connection

commit()

Dummy commit

cursor()

Dummy cursor function

rollback()

Dummy rollback

class retriever.lib.dummy.DummyCursor

Bases: retriever.lib.dummy.DummyConnection

Dummy connection cursor

retriever.lib.engine module

class retriever.lib.engine.Engine

Bases: object

A generic database system. Specific database platforms will inherit from this class.

add_to_table(data_source)

Adds data to a table from one or more lines specified in engine.table.source.

auto_create_table(table, url=None, filename=None, pk=None, make=True)

Create table automatically by analyzing a data source and predicting column names, data types, delimiter, etc.

auto_get_datatypes(pk, source, columns)

Determine data types for each column.

For string columns adds an additional 100 characters to the maximum observed value to provide extra space for cases where special characters are counted differently by different engines.

auto_get_delimiter(header)

Determine the delimiter.

Find out which of a set of common delimiters occurs most in the header line and use this as the delimiter.

check_bulk_insert()

Check if a bulk insert could be performed on the data

connect(force_reconnect=False)

Create a connection.

connection

Create a connection.

convert_data_type(datatype)

Convert Retriever generic data types to database platform specific data types.

create_db()

Create a new database based on settings supplied in Database object engine.db.

create_db_statement()

Return SQL statement to create a database.

create_raw_data_dir(path=None)

Check to see if the archive directory exists and creates it if necessary.

create_table()

Create new database table based on settings supplied in Table object engine.table.

create_table_statement()

Return SQL statement to create a table.

cursor

Get db cursor.

data_path = None

database_name(name=None)

Return name of the database.

datatypes = []

db = None

debug = False

disconnect()

Disconnect a connection.

disconnect_files()

Files systems should override this method.

Enables commit per file object.

download_file(url, filename)

Download file to the raw data directory.

download_files_from_archive(url, file_names=None, archive_type='zip', keep_in_dir=False, archive_name=None)

Download files from an archive into the raw data directory.

download_from_kaggle(data_source, dataset_name, archive_dir, archive_full_path)

Download files from Kaggle into the raw data directory

download_from_socrata(url, path, progbar)

Download files from Socrata to the raw data directory

download_response(url, path, progbar)

Returns True|None according to the download GET response

drop_statement(object_type, object_name)

Return drop table or database SQL statement.

encoding = None

excel_to_csv(src_path, path_to_csv, excel_info=None, encoding='utf-8')

Convert excel files to csv files.

execute(statement, commit=True)

Execute given statement.

executemany(statement, values, commit=True)

Execute given statement with multiple values.

extract_fixed_width(line)

Split line based on the fixed width, returns list of the values.

extract_gz(archive_path, archivedir_write_path, file_name=None, open_archive_file=None, archive=None)

Extract gz files.

Extracts a given file name or all the files in the gz.

extract_tar(archive_path, archivedir_write_path, archive_type, file_name=None)

Extract tar or tar.gz files.

Extracts a given file name or the file in the tar or tar.gz. # gzip archives can only contain a single file

extract_zip(archive_path, archivedir_write_path, file_name=None)

Extract zip files.

Extracts a given file name or the entire files in the archive.

fetch_tables(dataset, table_names)

This can be overridden to return the tables of sqlite db as pandas data frame. Return False by default.

final_cleanup()

Close the database connection.

find_file(filename)

Check for an existing datafile.

format_data_dir()

Return correctly formatted raw data directory location.

format_filename(filename)

Return full path of a file in the archive directory.

format_insert_value(value, datatype)

Format a value for an insert statement based on data type.

Different data types need to be formated differently to be properly stored in database management systems. The correct formats are obtained by:

1. Removing extra enclosing quotes
2. Harmonizing null indicators
3. Cleaning up badly formatted integers
4. Obtaining consistent float representations of decimals

get_connection()

This method should be overridden by specific implementations of Engine.

get_ct_data(lines)

Create cross tab data.

get_ct_line_length(lines)

Returns the number of real lines for cross-tab data

get_cursor()

Get db cursor.

get_input()

Manually get user input for connection information when script is run from terminal.

insert_data_from_archive(url, filenames)

Insert data from files located in an online archive. This function extracts the file, inserts the data, and deletes the file if raw data archiving is not set.

insert_data_from_file(filename)

The default function to insert data from a file. This function simply inserts the data row by row. Database platforms with support for inserting bulk data from files can override this function.

insert_data_from_url(url)

Insert data from a web resource, such as a text file.

insert_raster(path=None, srid=None)

Base function for installing raster data from path

insert_statement(values)

Return SQL statement to insert a set of values.

insert_vector(path=None, srid=None)

Base function for installing vector data from path

instructions = 'Enter your database connection information:'

load_data(filename)

Generator returning lists of values from lines in a data file.

1. Works on both delimited (csv module) and fixed width data (extract_fixed_width) 2. Identifies the delimiter if not known 3. Removes extra line ending

name = ''

pkformat = '%s PRIMARY KEY %s '

placeholder = None

process_geojson2csv(src_path, path_to_csv, encoding='utf-8')

process_hdf52csv(src_path, path_to_csv, data_name, data_type, encoding='utf-8')

process_json2csv(src_path, path_to_csv, headers, encoding='utf-8')

process_sqlite2csv(src_path, path_to_csv, table_name=None, encoding='utf-8')

Process sqlite database to csv files.

process_xml2csv(src_path, path_to_csv, header_values=None, empty_rows=1, encoding='utf-8')

register_tables()

Register table names of scripts

required_opts = []

script = None

script_table_registry = {}

set_engine_encoding()

Set up the encoding to be used.

set_table_delimiter(file_path)

Get the delimiter from the data file and set it.

spatial_support = False

supported_raster(path, ext=None)

“Spatial data is not currently supported for this database type or file format. PostgreSQL is currently the only supported output for spatial data.

table = None

table_name(name=None, dbname=None)

Return full table name.

to_csv(sort=True, path=None, select_columns=None, select_table=None)

Create a CSV file from the a data store.

sort flag to create a sorted file, path to write the flag else write to the PWD, select_columns flag is used by large files to select columns data and has SELECT LIMIT 3.

use_cache = True

warning(warning)

Create a warning message using the current script and table.

warnings = []

write_fileobject(archivedir_write_path, file_name, file_obj=None, archive=None, open_object=False)

Write a file object from a archive object to a given path

open_object flag helps up with zip files, open the zip and the file

retriever.lib.engine.file_exists(path)

Return true if a file exists and its size is greater than 0.

retriever.lib.engine.filename_from_url(url)

Extract and returns the filename from the url.

retriever.lib.engine.gen_from_source(source)

Return generator from a source tuple.

Source tuples are of the form (callable, args) where callable(star args) returns either a generator or another source tuple. This allows indefinite regeneration of data sources.

retriever.lib.engine.reporthook(tqdm_inst, filename=None)

tqdm wrapper to generate progress bar for urlretriever

retriever.lib.engine.set_csv_field_size()

Set the CSV size limit based on the available resources

retriever.lib.engine.skip_rows(rows, source)

Skip over the header lines by reading them before processing.

retriever.lib.engine_tools module

Data Retriever Tools

This module contains miscellaneous classes and functions used in Retriever scripts.

retriever.lib.engine_tools.create_file(data, output='output_file')

Write lines to file from a list.

retriever.lib.engine_tools.create_home_dir()

Create Directory for retriever.

retriever.lib.engine_tools.file_2list(input_file)

Read in a csv file and return lines a list.

retriever.lib.engine_tools.geojson2csv(input_file, output_file, encoding)

Convert Geojson file to csv.

Function is used for testing only.

retriever.lib.engine_tools.getmd5(data, data_type='lines', encoding='utf-8')

Get MD5 of a data source.

retriever.lib.engine_tools.hdf2csv(file, output_file, data_name, data_type, encoding='utf-8')

retriever.lib.engine_tools.json2csv(input_file, output_file=None, header_values=None, encoding='utf-8', row_key=None)

Convert Json file to CSV.

retriever.lib.engine_tools.reset_retriever(scope='all', ask_permission=True)

Remove stored information on scripts and data.

retriever.lib.engine_tools.set_proxy()

Check for proxies and makes them available to urllib.

retriever.lib.engine_tools.sort_csv(filename, encoding='utf-8')

Sort CSV rows minus the header and return the file.

Function is used for only testing and can handle the file of the size.

retriever.lib.engine_tools.sort_file(file_path, encoding='utf-8')

Sort file by line and return the file.

Function is used for only testing and can handle the file of the size.

retriever.lib.engine_tools.sqlite2csv(input_file, output_file, table_name=None, encoding='utf-8')

Convert sqlite database file to CSV.

retriever.lib.engine_tools.walker(raw_data, row_key=None, header_values=None, rows=[], normalize=False)

Extract rows of data from json datasets

retriever.lib.engine_tools.xml2csv(input_file, output_file, header_values=None, empty_rows=1, encoding='utf-8')

Convert xml to csv.

retriever.lib.engine_tools.xml2csv_test(input_file, outputfile=None, header_values=None, row_tag='row')

Convert xml to csv.

Function is used for only testing and can handle the file of the size.

retriever.lib.engine_tools.xml2dict(data, node, level)

Convert xml to dict type.

retriever.lib.excel module

Data Retriever Excel Functions

This module contains optional functions for importing data from Excel.

class retriever.lib.excel.Excel

Bases: object

Excel class to handle excel values

static cell_value(cell)

Return string value of an excel spreadsheet cell.

static empty_cell(cell)

Test if excel cell is empty or contains only whitespace.

retriever.lib.fetch module

retriever.lib.fetch.fetch(dataset, file='sqlite.db', table_name='{db}_{table}', data_dir='.')

Import a dataset into pandas data frames

retriever.lib.get_opts module

retriever.lib.install module

retriever.lib.install.install_csv(dataset, table_name='{db}_{table}.csv', data_dir='.', debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into csv.

retriever.lib.install.install_hdf5(dataset, file='hdf5.h5', table_name='{db}_{table}', data_dir='.', debug=False, use_cache=True, hash_value=None)

Install datasets into hdf5.

retriever.lib.install.install_json(dataset, table_name='{db}_{table}.json', data_dir='.', debug=False, use_cache=True, pretty=False, force=False, hash_value=None)

Install datasets into json.

retriever.lib.install.install_msaccess(dataset, file='access.mdb', table_name='[{db} {table}]', data_dir='.', debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into msaccess.

retriever.lib.install.install_mysql(dataset, user='root', password='', host='localhost', port=3306, database_name='{db}', table_name='{db}.{table}', debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into mysql.

retriever.lib.install.install_postgres(dataset, user='postgres', password='', host='localhost', port=5432, database='postgres', database_name='{db}', table_name='{db}.{table}', bbox=[], debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into postgres.

retriever.lib.install.install_sqlite(dataset, file='sqlite.db', table_name='{db}_{table}', data_dir='.', debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into sqlite.

retriever.lib.install.install_xml(dataset, table_name='{db}_{table}.xml', data_dir='.', debug=False, use_cache=True, force=False, hash_value=None)

Install datasets into xml.

retriever.lib.load_json module

retriever.lib.load_json.read_json(json_file)

Read Json dataset package files

Load each json and get the appropriate encoding for the dataset Reload the json using the encoding to ensure correct character sets

retriever.lib.models module

Data Retriever Data Model

This module contains basic class definitions for the Retriever platform.

retriever.lib.provenance module

retriever.lib.provenance.commit(dataset, commit_message='', path=None, quiet=False)

Commit dataset to a zipped file.

retriever.lib.provenance.commit_info_for_commit(dataset, commit_message, encoding='utf-8')

Generate info for a particular commit.

retriever.lib.provenance.commit_info_for_installation(metadata_info)

Returns a dictionary with commit info and changes in old and current environment

retriever.lib.provenance.commit_log(dataset)

Shows logs for a committed dataset which is in provenance directory

retriever.lib.provenance.commit_writer(dataset, commit_message, path, quiet)

Creates the committed zipped file

retriever.lib.provenance.install_committed(path_to_archive, engine, force=False, quiet=False)

Installs the committed dataset

retriever.lib.provenance.installation_details(metadata_info, quiet)

Outputs details of the commit for eg. commit message, time, changes in environment

retriever.lib.provenance.package_details()

Returns a dictionary with details of installed packages in the current environment

retriever.lib.provenance_tools module

retriever.lib.provenance_tools.get_metadata(path_to_archive)

Returns a dictionary after reading metadata.json file of a committed dataset

retriever.lib.provenance_tools.get_script_provenance(path_to_archive)

Reads script from archive.

retriever.lib.rdatasets module

retriever.lib.rdatasets.create_rdataset(engine, package, dataset_name, script_path=None)

Download files for RDatasets to the raw data directory

retriever.lib.rdatasets.display_all_rdataset_names(package_name=None)

displays the list of rdataset names present in the package(s) provided

retriever.lib.rdatasets.get_rdataset_names()

returns a list of all the available RDataset names present

retriever.lib.rdatasets.update_rdataset_catalog(test=False)

Updates the datasets_url.json from the github repo

retriever.lib.rdatasets.update_rdataset_contents(data_obj, package, dataset_name, json_file)

Update the contents of json script

retriever.lib.rdatasets.update_rdataset_script(data_obj, dataset_name, package, script_path)

Renames and updates the RDataset script

retriever.lib.repository module

Checks the repository for updates.

retriever.lib.repository.check_for_updates(repo='https://raw.githubusercontent.com/weecology/retriever-recipes/main/')

Check for updates to datasets.

This updates the HOME_DIR scripts directory with the latest script versions

retriever.lib.scripts module

retriever.lib.scripts.SCRIPT_LIST()

Return Loaded scripts.

Ensure that only one instance of SCRIPTS is created.

class retriever.lib.scripts.StoredScripts

Bases: object

Stored scripts class

get_scripts()

Return shared scripts

set_scripts(script_list)

Set shared scripts

retriever.lib.scripts.check_retriever_minimum_version(module)

Return true if a script’s version number is greater than the retriever’s version.

retriever.lib.scripts.get_data_upstream(search_url)

Basic method for getting upstream data

retriever.lib.scripts.get_dataset_names_upstream(keywords=None, licenses=None, repo='https://raw.githubusercontent.com/weecology/retriever-recipes/main/')

Search all datasets upstream by keywords and licenses. If the keywords or licenses argument is passed, Github’s search API is used for looking in the repositories. Else, the version.txt file is read and the script names are then returned.

retriever.lib.scripts.get_retriever_citation()

retriever.lib.scripts.get_retriever_script_versions()

Return the versions of the present local scripts

retriever.lib.scripts.get_script(dataset)

Return the script for a named dataset.

retriever.lib.scripts.get_script_citation(dataset=None)

Get the citation list for a script

retriever.lib.scripts.get_script_upstream(dataset, repo='https://raw.githubusercontent.com/weecology/retriever-recipes/main/')

Return the upstream script for a named dataset.

retriever.lib.scripts.get_script_version_upstream(dataset, repo='https://raw.githubusercontent.com/weecology/retriever-recipes/main/')

Return the upstream script version for a named dataset.

retriever.lib.scripts.name_matches(scripts, arg)

Check for a match of the script in available scripts

if all, return the entire script list if the exact script is available, return that script if no exact script name detected, match the argument with keywords title and name of all scripts and return the closest matches

retriever.lib.scripts.open_csvw(csv_file)

Open a csv writer forcing the use of Linux line endings on Windows.

Also sets dialect to ‘excel’ and escape characters to ‘’

retriever.lib.scripts.open_fr(file_name, encoding='utf-8', encode=True)

Open file for reading respecting Python version and OS differences.

Sets newline to Linux line endings on Windows and Python 3 When encode=False does not set encoding on nix and Python 3 to keep as bytes

retriever.lib.scripts.open_fw(file_name, encoding='utf-8', encode=True)

Open file for writing respecting Python version and OS differences.

Sets newline to Linux line endings on Python 3 When encode=False does not set encoding on nix and Python 3 to keep as bytes

retriever.lib.scripts.read_json_version(json_file)

Read the version of a script from a JSON file

retriever.lib.scripts.read_py_version(script_name, search_path)

Read the version of a script from a python file

retriever.lib.scripts.reload_scripts()

Load scripts from scripts directory and return list of modules.

retriever.lib.scripts.to_str(object, object_encoding=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, object_decoder='utf-8')

Convert to str

retriever.lib.socrata module

retriever.lib.socrata.create_socrata_dataset(engine, name, resource, script_path=None)

Downloads raw data and creates a script for the socrata dataset

retriever.lib.socrata.find_socrata_dataset_by_id(dataset_id)

Returns metadata for the following dataset id

retriever.lib.socrata.socrata_autocomplete_search(dataset)

Returns the list of dataset names after autocompletion

retriever.lib.socrata.socrata_dataset_info(dataset_name)

Returns the dataset information of the dataset name provided

retriever.lib.socrata.update_socrata_contents(json_file, script_name, url, resource)

Update the contents of the json script

retriever.lib.socrata.update_socrata_script(script_name, filename, url, resource, script_path)

Renames the script name and the contents of the script

retriever.lib.socrata.url_response(url, params)

Returns the GET response for the given url and params

retriever.lib.table module

class retriever.lib.table.Dataset(name=None, url=None)

Bases: object

Dataset generic properties

class retriever.lib.table.RasterDataset(name=None, url=None, dataset_type='RasterDataset', **kwargs)

Bases: retriever.lib.table.Dataset

Raster table implementation

class retriever.lib.table.TabularDataset(name=None, url=None, pk=True, contains_pk=False, delimiter=None, header_rows=1, column_names_row=1, fixed_width=False, cleanup=<retriever.lib.cleanup.Cleanup object>, record_id=0, columns=[], replace_columns=[], missingValues=None, cleaned_columns=False, number_of_records=None, **kwargs)

Bases: retriever.lib.table.Dataset

Tabular database table.

add_dialect()

Initialize dialect table properties.

These include a table’s null or missing values, the delimiter, the function to perform on missing values and any values in the dialect’s dict.

add_schema()

Add a schema to the table object.

Define the data type for the columns in the table.

auto_get_columns(header)

Get column names from the header row.

Identifies the column names from the header row. Replaces database keywords with alternatives. Replaces special characters and spaces.

clean_column_name(column_name)

Clean column names using the expected sql guidelines remove leading whitespaces, replace sql key words, etc.

combine_on_delimiter(line_as_list)

Combine a list of values into a line of csv data.

get_column_datatypes()

Get set of column names for insert statements.

get_insert_columns(join=True, create=False)

Get column names for insert statements.

create should be set to True if the returned values are going to be used for creating a new table. It includes the pk_auto column if present. This column is not included by default because it is not used when generating insert statements for database management systems.

values_from_line(line)

Return expected row values

Includes dynamically generated field values like auto pk

class retriever.lib.table.VectorDataset(name=None, url=None, dataset_type='VectorDataset', **kwargs)

Bases: retriever.lib.table.Dataset

Vector table implementation.

retriever.lib.templates module

Datasets are defined as scripts and have unique properties. The Module defines generic dataset properties and models the functions available for inheritance by the scripts or datasets.

class retriever.lib.templates.BasicTextTemplate(**kwargs)

Bases: retriever.lib.templates.Script

Defines the pre processing required for scripts.

Scripts that need pre processing should use the download function from this class. Scripts that require extra tune up, should override this class.

download(engine=None, debug=False)

Defines the download processes for scripts that utilize the default pre processing steps provided by the retriever.

process_archived_data(table_obj, url)

Pre-process archived files.

Archive info is specified for a single resource or entire data package. Extract the files from the archived source based on the specifications. Either extract a single file or all files. If the archived data is excel, use the xls_sheets to obtain the files to be extracted.

process_spatial_insert(table_obj)

Process spatial data for insertion

process_tables(table_obj, url)

Obtain the clean file and create a table

if xls_sheets, convert excel to csv Create the table from the file

process_tabular_insert(table_obj, url)

Process tabular data for insertion

class retriever.lib.templates.HtmlTableTemplate(title='', description='', name='', urls={}, tables={}, ref='', public=True, addendum=None, citation='Not currently available', licenses=[{'name': None}], retriever_minimum_version='', version='', encoding='utf-8', message='', **kwargs)

Bases: retriever.lib.templates.Script

Script template for parsing data in HTML tables.

class retriever.lib.templates.Script(title='', description='', name='', urls={}, tables={}, ref='', public=True, addendum=None, citation='Not currently available', licenses=[{'name': None}], retriever_minimum_version='', version='', encoding='utf-8', message='', **kwargs)

Bases: object

This class defines the properties of a generic dataset.

Each Dataset inherits attributes from this class to define it’s Unique functionality.

checkengine(engine=None)

Returns the required engine instance

download(engine=None, debug=False)

Generic function to prepare for installation or download.

matches_terms(terms)

Check if the terms matches a script metadata info

reference_url()

Get a reference url as the parent url from data url

retriever.lib.tools module

retriever.lib.tools.excel_csv(src_path, path_to_csv, excel_info=None, encoding='utf-8')

Convert an excel sheet to csv

Read src_path excel file and write the excel sheet to path_to_csv excel_info contains the index of the sheet and the excel file name

retriever.lib.tools.open_csvw(csv_file)

Open a csv writer forcing the use of Linux line endings on Windows.

Also sets dialect to ‘excel’ and escape characters to ‘’

retriever.lib.tools.open_fr(file_name, encoding='utf-8', encode=True)

Open file for reading respecting Python version and OS differences.

Sets newline to Linux line endings on Windows and Python 3 When encode=False does not set encoding on nix and Python 3 to keep as bytes

retriever.lib.tools.open_fw(file_name, encoding='utf-8', encode=True)

Open file for writing respecting Python version and OS differences.

Sets newline to Linux line endings on Python 3 When encode=False does not set encoding on nix and Python 3 to keep as bytes

retriever.lib.tools.to_str(object, object_encoding=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, object_decoder='utf-8')

Convert encoded values to string

retriever.lib.tools.walk_relative_path(dir_name)

Return relative paths of files in the directory

retriever.lib.warning module

class retriever.lib.warning.Warning(location, warning)

Bases: object

Custom warning class

Indices and tables

• Index
• Module Index
• Search Page