Group Case Study [Upgrad]
The case study is prepared for a Financial Institution called "Lending Club" based in USA which provides loan to the end consumers. As it always happens in most lending institution, Many are good loans whereas some are the bad loans. Few people tends to default their loan and not make timely payment or no payment at all to the organization.
This Case study is being prepared by putting ownself on the shoes of the person who is responsible for the approval and disbursement of the loan to the consumer. When a consumers comes and asks for a loan, we need to analyse past data and decide accordingly whether the person will be willing to pay back the loan in the future.
We should also not decline all the loan as it may cause the loss of business whereas accepting all the loans will increase probability of having more number of defaulters. To make the decision more accurate and precise, we will be analysing almost 40000 rows and 111 columns of the data.
All the rows and columns will not be required and also may result in irrelevancy in the decision, thus, we will find out such data and remove them accordingly.
- Numpy
- Pandas
- Matplotlib
- Seaborn
- Data Cleaning
- Univariate Analysis
- Segmented Univariate Analysis
- Bivariate Analysis
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