German_Credit: German Credit data set

In CollapseLevels: Collapses Levels, Computes Information Value and WoE

Description

This data set classifies customers as "Good" or "Bad" as per their credit risks.This data set was contributed by Professor Dr. Hans Hofmann,and can be downloaded from the UCI Machine Learning Repository.

Usage

data("German_Credit")

Format

A data frame with 1000 observations on the following 21 variables.

Account_Balance

a factor with levels A11 A12 A13 A14

Duration

a numeric vector

Credit_History

a factor with levels A30 A31 A32 A33 A34

Purpose

a factor with levels A40 A41 A410 A42 A43 A44 A45 A46 A48 A49

Credit_Amount

a numeric vector

Saving_Accounts_Bonds

a factor with levels A61 A62 A63 A64 A65

Current_Employment_Length

a factor with levels A71 A72 A73 A74 A75

Installment_Rate

a numeric vector

MaritalStatusnGender

a factor with levels A91 A92 A93 A94

Guarantors

a factor with levels A101 A102 A103

Duration in Current Address

a numeric vector

Valuable_Asset

a factor with levels A121 A122 A123 A124

Age

a numeric vector

Other_Credit

a factor with levels A141 A142 A143

Housing

a factor with levels A151 A152 A153

Existing_Credits

a numeric vector

Job

a factor with levels A171 A172 A173 A174

Dependents

a numeric vector

Telephone

a factor with levels A191 A192

ForeignWorker

a factor with levels A201 A202

Good_Bad

a numeric vector

Source

https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)

Examples

data(German_Credit)
str(German_Credit)

Example output

Loading required package: magrittr
'data.frame':	1000 obs. of  21 variables:
 $ Account_Balance            : Factor w/ 4 levels "A11","A12","A13",..: 1 2 4 1 1 4 4 2 4 2 ...
 $ Duration                   : int  6 48 12 42 24 36 24 36 12 30 ...
 $ Credit_History             : Factor w/ 5 levels "A30","A31","A32",..: 5 3 5 3 4 3 3 3 3 5 ...
 $ Purpose                    : Factor w/ 10 levels "A40","A41","A410",..: 5 5 8 4 1 8 4 2 5 1 ...
 $ Credit_Amount              : int  1169 5951 2096 7882 4870 9055 2835 6948 3059 5234 ...
 $ Saving_Accounts_Bonds      : Factor w/ 5 levels "A61","A62","A63",..: 5 1 1 1 1 5 3 1 4 1 ...
 $ Current_Employment_Length  : Factor w/ 5 levels "A71","A72","A73",..: 5 3 4 4 3 3 5 3 4 1 ...
 $ Installment_Rate           : int  4 2 2 2 3 2 3 2 2 4 ...
 $ MaritalStatusnGender       : Factor w/ 4 levels "A91","A92","A93",..: 3 2 3 3 3 3 3 3 1 4 ...
 $ Guarantors                 : Factor w/ 3 levels "A101","A102",..: 1 1 1 3 1 1 1 1 1 1 ...
 $ Duration in Current Address: int  4 2 3 4 4 4 4 2 4 2 ...
 $ Valuable_Asset             : Factor w/ 4 levels "A121","A122",..: 1 1 1 2 4 4 2 3 1 3 ...
 $ Age                        : int  67 22 49 45 53 35 53 35 61 28 ...
 $ Other_Credit               : Factor w/ 3 levels "A141","A142",..: 3 3 3 3 3 3 3 3 3 3 ...
 $ Housing                    : Factor w/ 3 levels "A151","A152",..: 2 2 2 3 3 3 2 1 2 2 ...
 $ Existing_Credits           : int  2 1 1 1 2 1 1 1 1 2 ...
 $ Job                        : Factor w/ 4 levels "A171","A172",..: 3 3 2 3 3 2 3 4 2 4 ...
 $ Dependents                 : int  1 1 2 2 2 2 1 1 1 1 ...
 $ Telephone                  : Factor w/ 2 levels "A191","A192": 2 1 1 1 1 2 1 2 1 1 ...
 $ ForeignWorker              : Factor w/ 2 levels "A201","A202": 1 1 1 1 1 1 1 1 1 1 ...
 $ Good_Bad                   : int  1 2 1 1 2 1 1 1 1 2 ...

CollapseLevels documentation built on July 1, 2020, 5:38 p.m.