About
This data details the creditworthiness of applicants based on the German Credit Data Set from the UCI Machine Learning Repository.
Data
credit_personal.csv
variable |
description |
credit_amount |
Credit amount in Deutsche Mark (DEM) |
age |
Age in years |
personal_status |
Marriage status and sex |
job |
Type of job |
employment |
Years since the present employment started |
savings_status |
Amount in DEM in savings account/bonds |
housing |
Housing status |
residence_since |
Present residence since |
property_magnitude |
Property type |
num_dependents |
Number of dependents |
own_telephone |
If an applicant owns a telephone |
foreign_worker |
If an applicant is a foreign worker |
credit_financial.csv
variable |
description |
checking |
Status of existing checking account |
duration |
Duration of credit in month |
credit_history |
Credit history |
purpose |
Purpose for credit |
installment_commitment |
Installment rate in percentage of disposable income |
other_parties |
Other debtors / guarantors |
other_payment_plans |
Other installment plans |
existing_credits |
Number of existing credits at this bank |
class |
Classification of good (1) or bad (2) credit risk |