German
Hugging FaceGerman The German dataset from the UCI ML repository. Dataset on loan grants to customers. Configurations and tasks Configuration Task Description encoding Encoding dictionary showing original values of encoded features. loan Binary classification Has the loan request been accepted? Usage from datasets import load_dataset dataset = load_dataset("mstz/german", "loan")["train"] Features Feature Type… See the full description on the dataset page: https://huggingface.co/datasets/mstz/german.
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Data preview
500 rows · 21 columns · showing first 12| # | checking_account_status integer | account_life_in_months integer | credit_status integer | loan_purpose text | current_credit integer | current_savings integer | employed_since integer | installment_rate_percentage integer | is_male boolean | marital_status integer | guarantors integer | years_living_in_current_residence integer | age integer | installment_plans integer | housing_status integer | nr_credit_accounts_in_bank integer | job_status integer | number_of_people_in_support integer | has_registered_phone_number integer | is_foreign boolean | loan_granted integer |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 6 | 4 | radio/television | 1169 | 0 | 4 | 4 | False | 1 | 0 | 4 | 67 | 2 | 2 | 2 | 2 | 1 | 1 | False | 0 |
| 2 | 2 | 48 | 2 | radio/television | 5951 | 1 | 2 | 2 | True | 0 | 0 | 2 | 22 | 2 | 2 | 1 | 2 | 1 | 0 | False | 1 |
| 3 | 0 | 12 | 4 | education | 2096 | 1 | 3 | 2 | False | 1 | 0 | 3 | 49 | 2 | 2 | 1 | 1 | 2 | 0 | False | 0 |
| 4 | 1 | 42 | 2 | furniture/equipment | 7882 | 1 | 3 | 2 | False | 1 | 2 | 4 | 45 | 2 | 0 | 1 | 2 | 2 | 0 | False | 0 |
| 5 | 1 | 24 | 3 | new car | 4870 | 1 | 2 | 3 | False | 1 | 0 | 4 | 53 | 2 | 0 | 2 | 2 | 2 | 0 | False | 1 |
| 6 | 0 | 36 | 2 | education | 9055 | 0 | 2 | 2 | False | 1 | 0 | 4 | 35 | 2 | 0 | 1 | 1 | 2 | 1 | False | 0 |
| 7 | 0 | 24 | 2 | furniture/equipment | 2835 | 3 | 4 | 3 | False | 1 | 0 | 4 | 53 | 2 | 2 | 1 | 2 | 1 | 0 | False | 0 |
| 8 | 2 | 36 | 2 | used car | 6948 | 1 | 2 | 2 | False | 1 | 0 | 2 | 35 | 2 | 1 | 1 | 3 | 1 | 1 | False | 0 |
| 9 | 0 | 12 | 2 | radio/television | 3059 | 4 | 3 | 2 | False | 0 | 0 | 4 | 61 | 2 | 2 | 1 | 1 | 1 | 0 | False | 0 |
| 10 | 2 | 30 | 4 | new car | 5234 | 1 | 0 | 4 | False | 2 | 0 | 2 | 28 | 2 | 2 | 2 | 3 | 1 | 0 | False | 1 |
| 11 | 2 | 12 | 2 | new car | 1295 | 1 | 1 | 3 | True | 0 | 0 | 1 | 25 | 2 | 1 | 1 | 2 | 1 | 0 | False | 1 |
| 12 | 1 | 48 | 2 | business | 4308 | 1 | 1 | 3 | True | 0 | 0 | 4 | 24 | 2 | 1 | 1 | 2 | 1 | 0 | False | 1 |
Interesting queries to try
- line chart of checking_account_status over account_life_in_months
- average checking_account_status by loan_purpose
- top 10 loan_purpose by total checking_account_status
- scatter checking_account_status vs credit_status coloured by loan_purpose
- histogram of checking_account_status
- boxplot of checking_account_status by loan_purpose
Columns
- checking_account_status numeric
- account_life_in_months datetime
- credit_status numeric
- loan_purpose categorical
- current_credit numeric
- current_savings numeric
- employed_since numeric
- installment_rate_percentage numeric
- is_male bool
- marital_status numeric
- guarantors numeric
- years_living_in_current_residence datetime
- age numeric
- installment_plans numeric
- housing_status numeric
- nr_credit_accounts_in_bank numeric
- job_status numeric
- number_of_people_in_support numeric
- has_registered_phone_number numeric
- is_foreign bool
- loan_granted numeric