Below is a data set that represents thousands of loans made through the Lending Club platform, which is a platform that allows individuals to lend to other individuals. We would like you to perform the following using the language of your choice: Describe the dataset and any issues with it. Generate a minimum of 5 unique visualizations using the data and write a brief description of your observations. Additionally, all attempts should be made to make the visualizations visually appealing Create a feature set and create a model which predicts interest rate using at least 2 algorithms. Describe any data cleansing that must be performed and analysis when examining the data. Visualize the test results and propose enhancements to the model, what would you do if you had more time. Also describe assumptions you made and your approach.

There is 1 dataset(csv) with 3 years’ worth of customer orders. There are 4 columns in the csv dataset: index, CUSTOMER_EMAIL (unique identifier as hash), Net Revenue, and Year.

For each year we need the following information:

• Total revenue for the current year
• New Customer Revenue e.g., new customers not present in previous year only
• Existing Customer Growth. To calculate this, use the Revenue of existing customers for current year –(minus) Revenue of existing customers from the previous year
• Revenue lost from attrition
• Existing Customer Revenue Current Year
• Existing Customer Revenue Prior Year
• Total Customers Current Year
• Total Customers Previous Year
• New Customers
• Lost Customers

Additionally, generate a few unique plots highlighting some information from the dataset. Are there any interesting observations? https://www.dropbox.com/sh/xhy2fzjdvg3ykhy/AADAVKH9tgD_dWh6TZtOd34ia?dl=0