germancredit: German Credit Data

In woeBinning: Supervised Weight of Evidence Binning of Numeric Variables and Factors

Description

Credit data that classifies debtors described by a set of attributes as good or bad credit risks. See source link below for detailed information.

Usage

data(germancredit)

Format

A data frame with 21 variables (numeric and factors) and 1000 observations.

Source

https://archive.ics.uci.edu/ml/datasets/Statlog+(German+Credit+Data)

Examples

# Load German credit data and create subset
data(germancredit)
df <- germancredit[, c('creditability', 'credit.amount', 'duration.in.month',
                  'savings.account.and.bonds', 'purpose')]
# Display structure of the subset (data frame)
str(df)

Example output

'data.frame':	1000 obs. of  5 variables:
 $ creditability            : Factor w/ 2 levels "bad","good": 2 1 2 2 1 2 2 2 2 1 ...
 $ credit.amount            : num  1169 5951 2096 7882 4870 ...
 $ duration.in.month        : num  6 48 12 42 24 36 24 36 12 30 ...
 $ savings.account.and.bonds: Factor w/ 5 levels "... < 100 DM",..: 5 1 1 1 1 5 4 1 2 1 ...
 $ purpose                  : Factor w/ 11 levels "business","car (new)",..: 8 8 5 6 2 5 6 3 8 2 ...

woeBinning documentation built on May 2, 2019, 9:23 a.m.