This is a final project submission for Udacity's 'Data Visualization with Matplotlib and Seaborn' course.
In this project, I explored loan listing data from a personal finance company, Prosper, using Python visualization libraries. My main goal was to investigate how different features in the dataset affect Borrower APR, and this question guided my analysis of single variables up through multivariate plots. The second part of this project is a short presentation of my findings: I put together some cleaned-up explanatory visualizations to communicate the properties, trends, and relationships my exploration uncovered.