Donors Choose Data Analysis

DonorsChoose.org has funded over 1.1 million classroom requests through the support of 3 million donors, the majority of whom were making their first-ever donation to a public school. If DonorsChoose.org can motivate even a fraction of those donors to make another donation, that could have a huge impact on the number of classroom requests fulfilled.

Data Source: https://www.kaggle.com/donorschoose/io

Attribute Information:

• project_id: A unique identifier for the proposed project.
• project_titlei: Title of the project.
• project_grade_category: Grade level of students for which the project is targeted.
• project_subject_categories: One or more (comma-separated) subject categories for the project.
• school_state: State where school is located (Two-letter U.S. postal code)
• project_subject_subcategories: One or more (comma-separated) subject subcategories for the project.
• project_resource_summary: An explanation of the resources needed for the project.
• project_essay_1/2/3/4: Application essay.
• teacher_id: A unique identifier for the teacher of the proposed project.
• teacher_prefix: nan, Dr./Mr./Mrs./Ms./Teacher
• teacher_number_of_previously_posted_projects: Number of project applications previously submitted by the same teacher.
• project_is_approved: A binary flag indicating whether DonorsChoose approved the project.A value of 0 indicates the project was not approved, and a value of 1 indicates the project was approved.

Objective:

The goal is to predict whether or not a DonorsChoose.org project proposal submitted by a teacher will be approved, using the text of project descriptions as well as additional metadata about the project, teacher, and school.

Prerequisites

You need to have installed following softwares and libraries before running this project.

1. Python 3: https://www.python.org/downloads/
2. Anaconda: It will install ipython notebook and most of the libraries which are needed like sklearn, pandas, seaborn, matplotlib, numpy and scipy: https://www.anaconda.com/download/

Getting Started

Start by downloading the project files and run the ".ipynb" file as a ipython-notebook (Jupyter notebook)

Requirements

• Required libraries are:
  • scikit-learn
  • numpy
  • pandas
  • matplotlib
  • nltk
  • python >= 3.7
  • Check the notebooks for more details

Author

• Manas Das