Founded in 2000 by a Bronx history teacher, DonorsChoose.org has raised $685 million for America's classrooms. Teachers at three-quarters of all the public schools in the U.S. have come to DonorsChoose.org to request what their students need, making DonorsChoose.org the leading platform for supporting public education.

To date, 3 million people and partners have funded 1.1 million DonorsChoose.org projects. But teachers still spend more than a billion dollars of their own money on classroom materials. To get students what they need to learn, the team at DonorsChoose.org needs to be able to connect donors with the projects that most inspire them.

The project aims to analyze complex data sets of DonorsChoose and provide recommendations to teacher about the top donors that may be willing to donate for a particular category.

This is done through analysis of historical data and listing the top donors with most number of contributions as a donor as well as the most amount donated.

To help teachers write proposal for their projects, bag of words using natural language processing is generated in Python after data pre-processing for this particular requirement.

The project also provides success rate for each category based on the donation amount received and the proect requirement cost which will help teachers select the best category according to their need.

Public data set can be found here:: https://www.kaggle.com/hanselhansel/donorschoose

!pip install chart_studio
!pip install matplotlib

• Basic Analysis

Contributions, issues, and feature requests are welcome!

To contribute to this project, see the GitHub documentation on creating a pull request.

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© 2021 Leah Nguyen