DATA4ECOLOGY

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Name:

Credit Card Balance Data

Description:

A simulated data set containing information on ten thousand customers. The aim here is to predict which customers will default on their credit card debt.

Variables:

A data frame with 10000 observations on the following 4 variables.

ID: Identification
Income: Income in $10,000's
Limit: Credit limit
Rating: Credit rating
Cards: Number of credit cards
Age: Age in years
Education: Number of years of education
Gender: A factor with levels Male and Female
Student: A factor with levels No and Yes indicating whether the individual was a student
Married: A factor with levels No and Yes indicating whether the individual was married
Ethnicity: A factor with levels African American, Asian, and Caucasian indicating the individual's ethnicity
Balance: Average credit card balance in $.

Link To Google Sheets:

Rows:

400

Columns:

Files:

Credit Card Balance Data_967_35.csv

License Type:

Public Domain (CC0)

References/Notes/Attributions:

Source

Simulated data, with thanks to Albert Kim for pointing out that this was omitted, and supplying the data and man documentation page on Oct 19, 2017

References

James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) An Introduction to Statistical Learning with applications in R, www.StatLearning.com, Springer-Verlag, New York

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