Dataset research report
German research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
German 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.
Research Context
German: 500 rows by 21 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Data Profile
Chart Evidence
These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.
Total checking_account_status by loan_purpose
Top loan_purpose values ranked by summed checking_account_status.
Open and export this chartchecking_account_status vs account_life_in_months
checking_account_status vs account_life_in_months, coloured by is_male.
Open and export this chartDistribution of checking_account_status
Histogram of checking_account_status values.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartchecking_account_status by loan_purpose
Spread of checking_account_status across loan_purpose groups.
Open and export this chartFollow-Up Queries
- 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
Preview Rows
| # | checking_account_statusinteger | account_life_in_monthsinteger | credit_statusinteger | loan_purposetext | current_creditinteger | current_savingsinteger | employed_sinceinteger | installment_rate_percentageinteger |
|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 6 | 4 | radio/television | 1169 | 0 | 4 | 4 |
| 2 | 2 | 48 | 2 | radio/television | 5951 | 1 | 2 | 2 |
| 3 | 0 | 12 | 4 | education | 2096 | 1 | 3 | 2 |
| 4 | 1 | 42 | 2 | furniture/equipment | 7882 | 1 | 3 | 2 |
| 5 | 1 | 24 | 3 | new car | 4870 | 1 | 2 | 3 |
| 6 | 0 | 36 | 2 | education | 9055 | 0 | 2 | 2 |
Data Dictionary
- 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
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.