Age Gender Housing Saving accounts Checking account Credit amount Duration
1 67 male own <NA> little 1169 6
2 22 female own little moderate 5951 48
3 49 male own little <NA> 2096 12
4 45 male free little little 7882 42
5 53 male free little little 4870 24
6 35 male free <NA> <NA> 9055 36
7 53 male own quite rich <NA> 2835 24
8 35 male rent little moderate 6948 36
9 61 male own rich <NA> 3059 12
10 28 male own little moderate 5234 30
Purpose Class Risk
1 radio/TV 1
2 radio/TV 2
3 education 1
4 furniture/equipment 1
5 car 2
6 education 1
7 furniture/equipment 1
8 car 1
9 radio/TV 1
10 car 2
Age Gender Housing Saving accounts Checking account Credit amount Duration
991 37 male own <NA> <NA> 3565 12
992 34 male own moderate <NA> 1569 15
993 23 male rent <NA> little 1936 18
994 30 male own little little 3959 36
995 50 male own <NA> <NA> 2390 12
996 31 female own little <NA> 1736 12
997 40 male own little little 3857 30
998 38 male own little <NA> 804 12
999 23 male free little little 1845 45
1000 27 male own moderate moderate 4576 45
Purpose Class Risk
991 education 1
992 radio/TV 1
993 radio/TV 1
994 furniture/equipment 1
995 car 1
996 furniture/equipment 1
997 car 1
998 radio/TV 1
999 radio/TV 2
1000 car 1
'data.frame': 1000 obs. of 9 variables:
$ Age : num 67 22 49 45 53 35 53 35 61 28 ...
$ Gender : chr "male" "female" "male" "male" ...
$ Housing : chr "own" "own" "own" "free" ...
$ Saving accounts : chr NA "little" "little" "little" ...
$ Checking account: chr "little" "moderate" NA "little" ...
$ Credit amount : num 1169 5951 2096 7882 4870 ...
$ Duration : num 6 48 12 42 24 36 24 36 12 30 ...
$ Purpose : chr "radio/TV" "radio/TV" "education" "furniture/equipment" ...
$ Class Risk : num 1 2 1 1 2 1 1 1 1 2 ...
