- Python 3
- Anaconda distribution to install Python, since the distribution includes all necessary Python libraries as well as Jupyter Notebooks.
- Numpy
- Pandas
- Matplotlib
- Seaborn
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This project is on a data set from Prosper, which is America’s first marketplace lending platform, with over $7 billion in funded loans. This data set contains 113,937 loans with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, borrower employment status, borrower credit history, and the latest payment information. The main purpose of this project is to summarize the characteristics of variables that can affect the loan status and to get some ideas about the relationships among multiple variables using summary statistics and data visualizations.
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The main purpose of this project is to summarize the characteristics of variables that can affect the loan status and to get some ideas about the relationships among multiple variables using summary statistics and data visualizations.