This dataset contains information about 113,937 loans represented by 81 features such as the loan amount, the monthly income, the employment status, and the loan status.

• The amount of loan is affected by the listed category of the loan. Most loans with high loan amount are rejected. However, in some categories, higher loans are completed. I believe this is related to how important is that category. Moreover, higher loans tend to be completed in cases of adoption or medical/dental categories which are important human needs.
• I investigated whether the employment status also is a factor. I found that high loans are defaulted more often in all employment categories. However, I found that self-employed borrowers tend to request the highest loan amount.

• Relationship between the loan status, the monthly income, and the loan amount.
• The relation between all the numeric features of interest.