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

data(germancredit)

Format

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

Examples

# load German credit data
data(germancredit)

# structure of germancredit
str(germancredit)
#> 'data.frame':	1000 obs. of  21 variables:
#>  $ status.of.existing.checking.account                     : Factor w/ 4 levels "... < 0 DM","0 <= ... < 200 DM",..: 1 2 4 1 1 4 4 2 4 2 ...
#>  $ duration.in.month                                       : num  6 48 12 42 24 36 24 36 12 30 ...
#>  $ credit.history                                          : Factor w/ 5 levels "no credits taken/ all credits paid back duly",..: 5 3 5 3 4 3 3 3 3 5 ...
#>  $ purpose                                                 : chr  "radio/television" "radio/television" "education" "furniture/equipment" ...
#>  $ credit.amount                                           : num  1169 5951 2096 7882 4870 ...
#>  $ savings.account.and.bonds                               : Factor w/ 5 levels "... < 100 DM",..: 5 1 1 1 1 5 3 1 4 1 ...
#>  $ present.employment.since                                : Factor w/ 5 levels "unemployed","... < 1 year",..: 5 3 4 4 3 3 5 3 4 1 ...
#>  $ installment.rate.in.percentage.of.disposable.income     : num  4 2 2 2 3 2 3 2 2 4 ...
#>  $ personal.status.and.sex                                 : Factor w/ 5 levels "male : divorced/separated",..: 1 1 1 1 1 1 1 1 1 1 ...
#>  $ other.debtors.or.guarantors                             : Factor w/ 3 levels "none","co-applicant",..: 1 1 1 3 1 1 1 1 1 1 ...
#>  $ present.residence.since                                 : num  4 2 3 4 4 4 4 2 4 2 ...
#>  $ property                                                : Factor w/ 4 levels "real estate",..: 1 1 1 2 4 4 2 3 1 3 ...
#>  $ age.in.years                                            : num  67 22 49 45 53 35 53 35 61 28 ...
#>  $ other.installment.plans                                 : Factor w/ 3 levels "bank","stores",..: 3 3 3 3 3 3 3 3 3 3 ...
#>  $ housing                                                 : Factor w/ 3 levels "rent","own","for free": 2 2 2 3 3 3 2 1 2 2 ...
#>  $ number.of.existing.credits.at.this.bank                 : num  2 1 1 1 2 1 1 1 1 2 ...
#>  $ job                                                     : Factor w/ 4 levels "unemployed/ unskilled - non-resident",..: 3 3 2 3 3 2 3 4 2 4 ...
#>  $ number.of.people.being.liable.to.provide.maintenance.for: num  1 1 2 2 2 2 1 1 1 1 ...
#>  $ telephone                                               : Factor w/ 2 levels "none","yes, registered under the customers name": 2 1 1 1 1 2 1 2 1 1 ...
#>  $ foreign.worker                                          : Factor w/ 2 levels "yes","no": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ creditability                                           : Factor w/ 2 levels "bad","good": 2 1 2 2 1 2 2 2 2 1 ...

# summary of germancredit
# lapply(germancredit, summary)