Loans Dataset

Dataset Description
Overview:
This dataset is designed for analysis and modeling in the context of loan lending and borrowing activities. It contains records of individual loan applications, approvals, and repayments, along with customer and loan-specific attributes.

Columns:
Loan_ID:

Description: A unique identifier for each loan application.
Data Type: String
Example Values: "LOAN001", "LOAN002", etc.
Customer_ID:

Description: A unique identifier for each customer.
Data Type: String
Example Values: "CUST001", "CUST002", etc.
Gender:

Description: The gender of the customer.
Data Type: Categorical
Values: "Male", "Female", "Other"
Married:

Description: Indicates whether the customer is married.
Data Type: Binary
Values: 0 (No), 1 (Yes)
Dependents:

Description: The number of dependents the customer has.
Data Type: Integer
Values: 0, 1, 2, etc.
Education:

Description: The highest level of education attained by the customer.
Data Type: Categorical
Values: "Graduate", "Not Graduate"
Self_Employed:

Description: Indicates whether the customer is self-employed.
Data Type: Binary
Values: 0 (No), 1 (Yes)
Applicant_Income:

Description: The applicant's monthly income.
Data Type: Float
Values: Positive numerical values.
Coapplicant_Income:

Description: The co-applicant's monthly income (if any).
Data Type: Float
Values: Positive numerical values, including zero.
Loan_Amount:

Description: The amount of loan approved.
Data Type: Float
Values: Positive numerical values.
Loan_Term:

Description: The term of the loan in months.
Data Type: Integer
Values: 12, 24, 36, etc.
Credit_History:

Description: The credit history of the applicant.
Data Type: Binary
Values: 0 (Not satisfactory), 1 (Satisfactory)
Property_Area:

Description: The type of area where the