diversedata 1.0.2

A Python package that provides a curated collection of real-world data sets centered on themes of equity, diversity and inclusion (EDI). These data sets are intended to support teaching, learning, and analysis by offering meaningful and socially relevant data that can be used in data science workflows.

diversedata

diversedata is a Python package that provides a curated collection of real-world data sets centered on themes of equity, diversity and inclusion (EDI). These data sets are intended to support teaching, learning, and analysis by offering meaningful and socially relevant data that can be used in data science workflows.

Each data set includes contextual background and documentation to support thoughtful exploration. Example use cases are included to demonstrate practical applications in R and Python are available on the website.

For more information, please visit: https://diverse-data-hub.github.io/

Installation

The diversedata Python package can be installed via pip:

pip install diversedata

Usage

Once installed, you can explore the available data sets and their documentation:

import diversedata as dd

# List available datasets
dd.list_available_datasets()

# View documentation for a specific dataset
dd.print_data_description('wildfire')

# To load a dataset and save it to an object:
df = dd.load_data('wildfire')

Package Dependencies

This package has the following dependency:

• pandas>=2.3.1

Please note that this dependency will be installed automatically when pip installing the diversedata package.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

diversedata was created by Katie Burak, Elham E. Khoda, and Stephanie Ta. It is licensed under the terms of the MIT license and Creative Commons Attribution 4.0 International license.

Data sets used in this project are licensed by their respective original creators, as indicated on each data set’s individual page. These data sets may have been adapted for use within this project.

Credits

diversedata was created with cookiecutter and the py-pkgs-cookiecutter template.