Prosper Loan Data Analysis is the project for the Communicate Data Findings portion of the Udacity Data Analyst Nanodegree program. In it loan data from Prosper is cleaned and then analyzed using visualizations.
In this project a dataset containing information for 113,937 loans from Prosper are analyzed using various visualization techniques in matplotlib and seaborn. The focus is on the variables of loan amount, borrower rate, and loan status, and progresses through an initial exploration of the data set, univariate, bivariate, and multivariate analysis of the data, and finally conclusions and explanatory visualizations of the relationships found. The Prosper Loan Data - Variable Definitions - Sheet1.csv file contains detailed descriptions of the variables in the initial data set provided. The prosper_clean.csv file is the cleaned file used in the data analysis portion of the project in the Jupyter Notebook. The prosper_pastdue_clean.csv file is a cleaned file of just listings with a LoanStatus of 'Past Due', that is used in certain portions of the data analysis in the project.The prosper_loan_data_analysis.html file is a copy of the Jupyter Notebook used when submitting this project. The output_toggle.tpl file is included to use the Jupyter Notebook as a slideshow. The slide_deck.ipynb and slide_deck.slides.html files are a copy of the slideshow created from the project. The readme_old.md was a summary of the project used during submission, but will be replaced by this README.md file
This code depends on the following libraries:
pandasnumpymatplotlib.pyplotseabornos
In addition to these, the Jupyter Notebook, prosper_loan_data_analysis.ipynb assumes that the data sets prosper_clean.csv and prosper_pastdue_clean.csv have been downloaded, extracted, and saved in the project folder.
The Binder badge above can be used to explore an executable environment for this project.
- add features section to README
- rename and organize files in project folder
- review and replace
readme_old.md - update slideshow files
- revise README
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