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---
dataset_info:
  features:
  - name: ID
    dtype: int64
  - name: AGE
    dtype: int64
  - name: INCOME
    dtype: int64
  - name: GENDER
    dtype: string
  - name: MARITAL
    dtype: string
  - name: NUMKIDS
    dtype: int64
  - name: NUMCARDS
    dtype: int64
  - name: HOWPAID
    dtype: string
  - name: MORTGAGE
    dtype: string
  - name: STORECAR
    dtype: int64
  - name: LOANS
    dtype: int64
  - name: RISK
    dtype: string
  splits:
  - name: train
    num_bytes: 255320
    num_examples: 2455
  download_size: 45820
  dataset_size: 255320
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Dataset Card for CreditCardRisk Dataset

## Dataset Summary
The CreditCardRisk Dataset is an English Language dataset containing 2455 entries of customer information and the associated credit card risk



## Dataset Structure

### Data Instances
For each instance, there is an integer for the ID , an integer for the age, an integer for the income, a string for the gender with 2 possible values m for male and f for female, a string for the marital status with 3 possible values: married, single, divsepwid (represents divorced, separated, widow), an integer for the numkids, an integer for the numcards, a string for the howpaid with 2 possible values, weekly or monthly, a string for the mortgage with 2 possible values y (yes) or n (no), an integer for the storecar, an integer for the loans, and a string for the risk with 3 possible values, bad profit, bad loss, or good risk.

{'ID': '100,756',
 'AGE': '44',
 'INCOME': '59,944',
 'GENDER': 'm',
 'MARITAL': 'married',
 'NUMKIDS': '1',
 'NUMCARDS': '2',
 'HOWPAID': 'monthly',
 'MORTGAGE': 'y',
 'STORECAR': '2',
 'LOANS': '0',
 'RISK': 'good risk',
 }

### Data Fields
- **ID:** an integer with a unique ID for each customer
- **AGE:** an integer stating the age of the customer
- **INCOME:** an integer stating the income of the customer in USD
- **GENDER:** a string stating the gender of the customer with 2 possible values, either m (male) or f (female)
- **MARITAL:** a string stating the marital status of the customer 3 possible values, either married, single, or divsepwid
- **NUMKIDS:** an integer stating the number of children each customer has
- **NUMCARDS:** an integer stating the number of cards each customer has
- **HOWPAID:** a string stating the frequency of payment received by each customer with 2 possible values, monthly or weekly
- **MORTGAGE:** a string stating whether a customer has mortgage with 2 possible values, y or no
- **STORECAR:** an integer stating the number of store credit cards each customer has
- **LOANS:** an integer stating the number of outstanding loans each customer has 
- **RISK:** a string stating the credit card risk per customer with 3 possible values, bad loss, bad profit or good risk


### Dataset Sources
IBM Academic Initiative Program

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- **Repository:** [More Information Needed]
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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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