BSAD343 Assignment 3
CME Group Foundation Business Analytics Lab
Your Name Here
Add Date Here
mydata = read.csv(file="data/creditrisk.csv") #Reading csv file
mydata #calling csv file## Loan.Purpose Checking Savings Months.Customer Months.Employed
## 1 Small Appliance 0 739 13 12
## 2 Furniture 0 1230 25 0
## 3 New Car 0 389 19 119
## 4 Furniture 638 347 13 14
## 5 Education 963 4754 40 45
## 6 Furniture 2827 0 11 13
## 7 New Car 0 229 13 16
## 8 Business 0 533 14 2
## 9 Small Appliance 6509 493 37 9
## 10 Small Appliance 966 0 25 4
## 11 Business 0 989 49 0
## 12 New Car 0 3305 11 15
## 13 Business 322 578 10 14
## 14 New Car 0 821 25 63
## 15 New Car 396 228 13 26
## 16 Used Car 0 129 31 8
## 17 Furniture 652 732 49 4
## 18 New Car 708 683 13 33
## 19 Repairs 207 0 28 116
## 20 Education 287 12348 7 2
## 21 Furniture 0 17545 34 16
## 22 Furniture 101 3871 13 5
## 23 Furniture 0 0 25 23
## 24 Furniture 0 485 37 23
## 25 New Car 0 10723 11 15
## 26 Business 141 245 22 33
## 27 Used Car 0 0 19 58
## 28 Used Car 2484 0 49 46
## 29 Small Appliance 237 236 37 24
## 30 Small Appliance 0 485 19 12
## 31 Education 335 1708 37 7
## 32 Small Appliance 3565 0 31 32
## 33 Small Appliance 0 407 13 2
## 34 Business 16647 895 16 34
## 35 Business 0 150 49 46
## 36 Small Appliance 0 490 5 41
## 37 Furniture 0 162 25 1
## 38 Small Appliance 940 715 9 40
## 39 Small Appliance 0 323 49 42
## 40 New Car 0 128 13 74
## 41 Other 218 0 49 0
## 42 Used Car 0 109 25 26
## 43 Small Appliance 16935 189 37 60
## 44 Furniture 664 537 31 33
## 45 Furniture 150 6520 12 1
## 46 Small Appliance 0 138 7 119
## 47 Furniture 216 0 19 3
## 48 New Car 0 660 17 75
## 49 Business 0 724 25 8
## 50 Small Appliance 0 897 19 5
## 51 Small Appliance 265 947 25 5
## 52 Furniture 4256 0 16 36
## 53 Business 870 917 28 6
## 54 New Car 162 595 22 10
## 55 Used Car 0 789 25 28
## 56 Education 0 0 37 114
## 57 Furniture 0 746 13 16
## 58 New Car 461 140 19 32
## 59 New Car 0 659 19 5
## 60 Furniture 0 717 37 60
## 61 New Car 0 667 29 10
## 62 New Car 580 0 11 8
## 63 Small Appliance 0 763 13 46
## 64 New Car 0 1366 19 17
## 65 Small Appliance 0 552 25 4
## 66 Small Appliance 0 14643 16 115
## 67 Business 758 2665 13 31
## 68 Used Car 399 0 31 0
## 69 Furniture 513 442 7 0
## 70 Furniture 0 8357 25 5
## 71 New Car 0 0 22 9
## 72 Small Appliance 565 863 10 81
## 73 Business 0 322 28 28
## 74 Furniture 0 800 13 69
## 75 Small Appliance 0 656 37 85
## 76 New Car 166 922 13 2
## 77 Business 9783 885 13 3
## 78 Business 674 2886 49 32
## 79 Repairs 0 626 43 0
## 80 Business 15328 0 25 9
## 81 New Car 0 904 12 6
## 82 Education 713 784 61 17
## 83 New Car 0 806 19 3
## 84 Education 0 3281 19 20
## 85 New Car 0 759 16 59
## 86 Small Appliance 0 680 25 3
## 87 Used Car 0 104 37 25
## 88 Small Appliance 303 899 13 3
## 89 Small Appliance 900 1732 37 11
## 90 Furniture 0 706 31 14
## 91 Education 1257 0 10 65
## 92 Small Appliance 0 576 7 14
## 93 Repairs 273 904 7 2
## 94 Business 522 194 25 79
## 95 Small Appliance 0 710 25 1
## 96 Small Appliance 0 5564 25 93
## 97 Small Appliance 0 192 46 13
## 98 New Car 0 637 13 21
## 99 Small Appliance 514 405 49 13
## 100 Furniture 457 318 19 108
## 101 Small Appliance 5133 698 19 14
## 102 New Car 0 369 10 16
## 103 Retraining 644 0 13 88
## 104 Furniture 305 492 19 1
## 105 New Car 9621 308 25 41
## 106 Education 0 127 13 22
## 107 Business 0 565 19 14
## 108 Furniture 0 12632 16 9
## 109 New Car 0 116 49 45
## 110 Used Car 0 178 13 89
## 111 Small Appliance 6851 901 13 21
## 112 Furniture 13496 650 19 20
## 113 Business 509 241 25 14
## 114 Used Car 0 609 37 6
## 115 Furniture 19155 131 25 24
## 116 Furniture 0 544 19 15
## 117 Small Appliance 0 10853 25 81
## 118 Used Car 374 0 25 14
## 119 Large Appliance 0 409 49 15
## 120 Furniture 828 391 9 12
## 121 Furniture 0 322 13 9
## 122 Small Appliance 829 583 7 18
## 123 Small Appliance 0 12242 25 53
## 124 Furniture 0 479 19 0
## 125 New Car 939 496 19 56
## 126 New Car 0 466 25 42
## 127 New Car 889 1583 37 79
## 128 Furniture 876 1533 31 21
## 129 Small Appliance 893 0 16 94
## 130 Business 12760 4873 13 73
## 131 Furniture 0 0 13 94
## 132 Small Appliance 0 717 22 10
## 133 Small Appliance 959 7876 28 20
## 134 Small Appliance 0 4449 25 87
## 135 Other 0 0 25 54
## 136 Business 0 104 25 23
## 137 Repairs 0 897 19 2
## 138 New Car 698 4033 16 20
## 139 Furniture 0 945 13 6
## 140 Furniture 0 836 25 99
## 141 Small Appliance 0 325 19 13
## 142 Small Appliance 12974 19568 13 7
## 143 Furniture 0 803 13 89
## 144 Small Appliance 317 10980 13 17
## 145 Business 0 265 13 10
## 146 Repairs 0 609 31 3
## 147 Small Appliance 0 1851 12 0
## 148 Furniture 192 199 25 5
## 149 New Car 0 500 28 7
## 150 New Car 0 509 16 3
## 151 Used Car 0 270 25 25
## 152 New Car 0 457 13 63
## 153 Used Car 0 260 25 78
## 154 New Car 942 3036 25 36
## 155 Small Appliance 0 643 19 6
## 156 New Car 3329 0 19 15
## 157 Used Car 0 6345 25 19
## 158 Education 0 922 37 9
## 159 Furniture 0 909 25 3
## 160 Large Appliance 0 775 19 8
## 161 Furniture 0 979 25 48
## 162 Furniture 0 948 19 2
## 163 Business 339 2790 22 55
## 164 Used Car 0 309 49 37
## 165 Small Appliance 0 762 10 1
## 166 Small Appliance 0 970 13 14
## 167 Used Car 105 320 28 54
## 168 Small Appliance 0 861 13 111
## 169 Repairs 216 262 37 2
## 170 Furniture 113 692 11 14
## 171 Used Car 109 540 37 1
## 172 New Car 0 470 13 0
## 173 New Car 0 192 7 2
## 174 New Car 8176 12230 7 5
## 175 Repairs 0 772 25 19
## 176 Furniture 468 14186 22 24
## 177 Used Car 7885 6330 16 14
## 178 Small Appliance 0 18716 19 93
## 179 New Car 0 886 22 96
## 180 Business 0 750 37 2
## 181 Small Appliance 0 3870 25 11
## 182 Small Appliance 0 3273 13 4
## 183 Business 0 406 6 35
## 184 Furniture 0 461 13 48
## 185 Furniture 0 340 19 4
## 186 Small Appliance 0 6490 19 85
## 187 Small Appliance 734 348 7 100
## 188 Furniture 0 506 25 3
## 189 Used Car 0 14717 28 7
## 190 Business 172 0 25 36
## 191 New Car 644 1571 19 1
## 192 New Car 0 0 25 19
## 193 Furniture 617 411 31 3
## 194 New Car 0 544 25 0
## 195 Small Appliance 586 0 13 0
## 196 Furniture 0 835 19 42
## 197 Small Appliance 0 823 25 47
## 198 Business 0 5180 22 4
## 199 Small Appliance 0 408 16 12
## 200 New Car 0 821 48 5
## 201 Education 522 385 10 66
## 202 New Car 585 2223 16 0
## 203 New Car 5588 0 22 10
## 204 New Car 0 605 37 20
## 205 Furniture 352 7525 13 4
## 206 Small Appliance 0 3529 14 0
## 207 Business 2715 1435 49 14
## 208 Other 560 887 25 20
## 209 Small Appliance 895 243 13 4
## 210 New Car 305 4553 7 2
## 211 Small Appliance 0 418 19 4
## 212 New Car 0 771 25 0
## 213 Furniture 0 463 11 13
## 214 Business 8948 110 31 90
## 215 Used Car 0 10099 16 108
## 216 Used Car 0 13428 7 0
## 217 Small Appliance 0 208 13 23
## 218 Small Appliance 0 552 13 15
## 219 Education 0 3105 16 19
## 220 Small Appliance 483 415 19 6
## 221 Large Appliance 0 1238 13 0
## 222 Education 0 238 13 2
## 223 Furniture 0 127 31 35
## 224 Business 663 0 19 57
## 225 New Car 624 785 37 9
## 226 Repairs 0 718 19 0
## 227 Furniture 0 493 13 21
## 228 Small Appliance 152 757 49 45
## 229 New Car 0 9125 13 24
## 230 Small Appliance 0 364 13 12
## 231 Business 498 598 37 14
## 232 New Car 0 374 10 19
## 233 Small Appliance 156 0 13 58
## 234 Used Car 1336 0 37 11
## 235 New Car 0 508 13 3
## 236 Small Appliance 0 956 25 4
## 237 Furniture 0 636 22 41
## 238 New Car 2641 0 13 71
## 239 Used Car 0 1519 40 74
## 240 Business 0 922 19 29
## 241 Furniture 0 180 5 2
## 242 Used Car 0 701 22 108
## 243 Small Appliance 0 296 16 8
## 244 Small Appliance 887 519 7 42
## 245 Business 0 800 49 2
## 246 Furniture 0 736 13 6
## 247 Small Appliance 0 11838 7 70
## 248 Small Appliance 0 364 5 35
## 249 New Car 18408 212 13 9
## 250 New Car 497 888 16 3
## 251 Used Car 0 999 25 0
## 252 Small Appliance 946 0 16 83
## 253 Business 986 578 28 1
## 254 Education 8122 136 22 4
## 255 Furniture 0 734 37 111
## 256 Business 778 861 49 21
## 257 Other 645 855 25 17
## 258 Furniture 0 4486 10 3
## 259 New Car 682 2017 37 85
## 260 New Car 19812 0 25 37
## 261 Business 0 500 25 1
## 262 Used Car 0 859 31 89
## 263 Business 859 3305 25 26
## 264 Small Appliance 0 1218 13 38
## 265 New Car 0 9016 49 22
## 266 New Car 0 11587 22 46
## 267 Furniture 0 8944 25 66
## 268 Repairs 0 807 25 75
## 269 Small Appliance 0 867 31 27
## 270 Small Appliance 795 16804 49 40
## 271 Furniture 0 347 16 5
## 272 Furniture 0 836 16 4
## 273 Furniture 0 142 7 53
## 274 Furniture 0 169 19 6
## 275 Other 852 3613 61 83
## 276 Education 0 403 7 5
## 277 Small Appliance 0 836 25 0
## 278 New Car 425 0 19 7
## 279 Business 0 11481 25 18
## 280 Business 0 3285 7 21
## 281 Education 0 164 13 65
## 282 New Car 11072 891 61 17
## 283 Used Car 0 0 37 49
## 284 Used Car 219 841 43 0
## 285 New Car 8060 607 19 71
## 286 New Car 0 486 12 22
## 287 New Car 0 108 25 52
## 288 Small Appliance 0 0 43 28
## 289 New Car 0 113 25 31
## 290 New Car 1613 0 25 118
## 291 Furniture 757 208 25 36
## 292 Retraining 0 603 13 35
## 293 New Car 0 343 19 22
## 294 Education 977 463 10 61
## 295 Education 197 0 37 17
## 296 Furniture 0 299 19 11
## 297 New Car 0 490 13 15
## 298 Small Appliance 0 6628 37 65
## 299 Business 0 859 19 23
## 300 New Car 0 750 13 14
## 301 Small Appliance 256 954 10 13
## 302 New Car 296 591 37 103
## 303 Furniture 0 13970 13 24
## 304 New Car 0 857 11 34
## 305 Furniture 0 5857 19 20
## 306 Small Appliance 298 3326 73 15
## 307 Small Appliance 0 726 19 7
## 308 Furniture 8636 214 11 3
## 309 New Car 0 207 13 119
## 310 New Car 0 713 13 29
## 311 New Car 19766 2141 11 54
## 312 New Car 0 483 19 90
## 313 New Car 0 127 7 13
## 314 Furniture 0 367 37 22
## 315 Small Appliance 0 813 43 28
## 316 Furniture 4089 0 7 14
## 317 New Car 0 102 7 0
## 318 Repairs 271 759 19 0
## 319 New Car 949 0 49 36
## 320 Small Appliance 0 503 13 62
## 321 Small Appliance 911 823 46 4
## 322 New Car 0 693 19 28
## 323 Used Car 0 973 49 81
## 324 New Car 0 648 15 57
## 325 Other 0 523 37 0
## 326 Used Car 271 7090 25 2
## 327 Small Appliance 0 596 13 67
## 328 Used Car 0 904 49 119
## 329 New Car 0 541 19 13
## 330 Furniture 0 154 37 2
## 331 New Car 4802 0 37 12
## 332 Business 177 0 49 9
## 333 Small Appliance 0 337 25 107
## 334 New Car 0 716 19 33
## 335 Education 996 837 49 83
## 336 Education 705 0 25 24
## 337 Furniture 0 7710 25 114
## 338 New Car 0 531 13 5
## 339 Small Appliance 5960 129 13 16
## 340 Furniture 0 941 13 111
## 341 Furniture 759 596 10 18
## 342 Furniture 0 987 37 101
## 343 Small Appliance 651 0 37 102
## 344 Business 257 460 49 75
## 345 Small Appliance 955 0 49 29
## 346 Small Appliance 0 798 25 42
## 347 Small Appliance 8249 0 31 77
## 348 Small Appliance 0 959 11 21
## 349 Small Appliance 956 1482 46 19
## 350 New Car 382 883 31 20
## 351 Furniture 0 12721 37 31
## 352 Education 842 0 37 9
## 353 Repairs 3111 0 13 27
## 354 Small Appliance 0 302 10 30
## 355 Furniture 0 538 25 59
## 356 Small Appliance 2846 0 13 14
## 357 Small Appliance 231 702 10 99
## 358 Repairs 0 2688 10 89
## 359 Small Appliance 17366 0 16 21
## 360 Small Appliance 0 425 13 10
## 361 New Car 332 214 25 2
## 362 Small Appliance 242 0 19 6
## 363 New Car 0 272 7 90
## 364 Business 929 124 9 1
## 365 Small Appliance 0 17124 13 95
## 366 Used Car 0 612 49 32
## 367 New Car 0 862 49 62
## 368 Furniture 0 146 25 46
## 369 New Car 0 14190 37 92
## 370 Used Car 0 396 49 73
## 371 Small Appliance 0 519 31 23
## 372 Used Car 646 0 25 9
## 373 New Car 538 344 13 40
## 374 Furniture 0 204 31 5
## 375 Small Appliance 0 148 43 2
## 376 Furniture 0 435 19 16
## 377 Small Appliance 0 914 19 0
## 378 New Car 135 0 37 7
## 379 Used Car 2472 0 37 41
## 380 New Car 0 412 25 22
## 381 New Car 10417 19811 13 27
## 382 Small Appliance 211 822 8 5
## 383 Small Appliance 16630 0 11 47
## 384 Furniture 0 3369 25 17
## 385 Furniture 642 0 13 65
## 386 Small Appliance 0 707 7 26
## 387 Small Appliance 296 818 19 93
## 388 Business 898 177 22 105
## 389 New Car 478 4071 10 40
## 390 New Car 315 466 13 3
## 391 New Car 122 460 37 109
## 392 Furniture 0 991 7 3
## 393 Small Appliance 0 17653 22 4
## 394 Education 0 497 41 24
## 395 Business 670 4014 31 21
## 396 Business 444 921 28 51
## 397 New Car 3880 0 23 37
## 398 Used Car 819 0 13 23
## 399 Used Car 0 607 37 17
## 400 Large Appliance 0 15800 16 40
## 401 Furniture 0 369 7 23
## 402 Business 0 4973 25 17
## 403 Furniture 0 0 40 30
## 404 New Car 0 761 25 92
## 405 Education 0 471 7 52
## 406 Used Car 0 674 37 69
## 407 New Car 0 547 13 40
## 408 Furniture 161 524 13 106
## 409 Furniture 0 815 19 13
## 410 Used Car 0 0 11 4
## 411 New Car 789 989 31 0
## 412 Small Appliance 765 10406 10 24
## 413 Furniture 0 957 19 11
## 414 New Car 0 770 37 3
## 415 Furniture 983 950 13 5
## 416 Used Car 0 160 13 7
## 417 Used Car 0 276 25 91
## 418 Education 798 137 25 25
## 419 New Car 0 579 22 70
## 420 New Car 193 2684 13 5
## 421 Small Appliance 497 0 7 51
## 422 Furniture 0 0 31 53
## 423 New Car 0 0 25 103
## 424 New Car 0 712 16 6
## 425 New Car 0 912 7 39
## Gender Marital.Status Age Housing Years Job Credit.Risk
## 1 M Single 23 Own 3 Unskilled Low
## 2 M Divorced 32 Own 1 Skilled High
## 3 M Single 38 Own 4 Management High
## 4 M Single 36 Own 2 Unskilled High
## 5 M Single 31 Rent 3 Skilled Low
## 6 M Married 25 Own 1 Skilled Low
## 7 M Married 26 Own 3 Unskilled Low
## 8 M Single 27 Own 1 Unskilled Low
## 9 M Single 25 Own 2 Skilled High
## 10 F Divorced 43 Own 1 Skilled High
## 11 M Single 32 Rent 2 Management High
## 12 M Single 34 Rent 2 Unskilled Low
## 13 M Married 26 Own 1 Skilled Low
## 14 M Single 44 Own 1 Skilled High
## 15 M Single 46 Own 3 Unskilled Low
## 16 M Divorced 39 Own 4 Management Low
## 17 F Divorced 25 Own 2 Skilled High
## 18 M Single 31 Own 2 Skilled Low
## 19 M Single 47 Own 4 Skilled Low
## 20 F Divorced 23 Rent 2 Skilled High
## 21 F Divorced 22 Own 4 Skilled High
## 22 F Divorced 26 Rent 4 Skilled High
## 23 M Married 19 Own 4 Skilled High
## 24 F Divorced 27 Own 2 Management High
## 25 M Single 39 Rent 2 Unskilled Low
## 26 M Single 26 Own 3 Skilled Low
## 27 M Single 50 Other 4 Skilled High
## 28 M Single 34 Other 1 Skilled Low
## 29 M Single 23 Rent 4 Skilled Low
## 30 M Single 23 Own 2 Skilled Low
## 31 M Single 46 Other 4 Skilled High
## 32 M Single 35 Own 3 Skilled Low
## 33 F Divorced 28 Own 2 Skilled Low
## 34 M Single 25 Rent 4 Skilled Low
## 35 F Divorced 36 Rent 4 Skilled High
## 36 M Single 41 Own 1 Unskilled Low
## 37 M Divorced 54 Own 1 Skilled High
## 38 F Divorced 43 Own 2 Unskilled Low
## 39 M Married 33 Own 1 Skilled High
## 40 M Single 34 Own 3 Skilled High
## 41 M Single 39 Other 4 Unemployed Low
## 42 M Single 34 Own 3 Unskilled Low
## 43 M Single 30 Own 2 Skilled Low
## 44 M Single 48 Own 2 Skilled High
## 45 F Divorced 19 Own 1 Skilled Low
## 46 M Married 29 Rent 2 Skilled Low
## 47 F Divorced 26 Rent 3 Skilled High
## 48 M Single 42 Rent 4 Skilled High
## 49 M Single 30 Rent 2 Skilled High
## 50 M Married 38 Own 4 Skilled Low
## 51 M Married 21 Own 1 Skilled High
## 52 F Divorced 32 Rent 4 Unskilled Low
## 53 M Single 35 Own 2 Skilled High
## 54 M Divorced 46 Own 4 Skilled Low
## 55 M Single 37 Own 3 Management Low
## 56 M Single 39 Own 4 Management High
## 57 F Divorced 29 Own 3 Skilled Low
## 58 M Single 27 Rent 3 Unskilled Low
## 59 F Divorced 22 Rent 3 Skilled High
## 60 M Single 40 Own 2 Skilled High
## 61 M Single 44 Own 2 Unskilled High
## 62 M Single 26 Own 4 Unskilled High
## 63 F Divorced 57 Own 3 Unskilled Low
## 64 M Single 34 Own 4 Unskilled Low
## 65 M Married 47 Own 4 Skilled High
## 66 M Single 46 Own 3 Skilled Low
## 67 M Single 38 Own 4 Unskilled Low
## 68 F Divorced 52 Own 1 Management High
## 69 M Single 34 Own 1 Management Low
## 70 M Single 29 Other 4 Skilled High
## 71 M Single 39 Own 2 Unskilled High
## 72 M Single 36 Own 4 Unskilled Low
## 73 M Single 25 Own 4 Skilled Low
## 74 M Single 59 Own 3 Skilled High
## 75 M Single 27 Own 2 Skilled Low
## 76 F Divorced 24 Rent 1 Skilled High
## 77 F Divorced 25 Own 1 Unemployed High
## 78 M Single 29 Own 2 Skilled Low
## 79 M Single 64 Own 4 Unemployed Low
## 80 M Single 31 Own 4 Skilled Low
## 81 M Single 38 Own 4 Unskilled Low
## 82 M Single 41 Other 4 Skilled High
## 83 F Divorced 22 Own 2 Unskilled High
## 84 F Divorced 29 Own 2 Skilled High
## 85 M Single 32 Rent 3 Skilled High
## 86 F Divorced 34 Own 4 Skilled High
## 87 M Single 23 Own 4 Skilled High
## 88 M Single 21 Own 1 Skilled High
## 89 F Divorced 49 Other 4 Skilled High
## 90 M Divorced 31 Own 2 Skilled Low
## 91 F Divorced 40 Rent 4 Unskilled Low
## 92 F Divorced 28 Own 1 Skilled Low
## 93 M Married 21 Own 1 Unskilled Low
## 94 M Divorced 30 Own 4 Skilled High
## 95 F Divorced 37 Own 3 Skilled Low
## 96 M Single 33 Own 2 Skilled Low
## 97 M Single 22 Other 4 Skilled High
## 98 F Divorced 23 Own 2 Unskilled High
## 99 F Divorced 21 Own 2 Skilled High
## 100 M Single 40 Own 1 Skilled Low
## 101 M Single 36 Own 2 Skilled High
## 102 M Single 29 Own 1 Skilled Low
## 103 M Single 37 Own 4 Skilled Low
## 104 F Divorced 26 Own 1 Skilled Low
## 105 M Single 37 Other 3 Skilled High
## 106 M Single 39 Rent 4 Unskilled High
## 107 M Married 27 Own 2 Skilled High
## 108 F Divorced 19 Rent 4 Skilled Low
## 109 M Single 45 Other 4 Skilled High
## 110 M Single 34 Other 4 Skilled High
## 111 F Divorced 43 Rent 2 Unskilled Low
## 112 M Single 33 Own 1 Unskilled High
## 113 M Single 35 Own 4 Unskilled High
## 114 M Single 31 Other 2 Management Low
## 115 M Single 25 Own 2 Skilled Low
## 116 F Divorced 27 Own 2 Skilled Low
## 117 F Divorced 56 Rent 4 Management Low
## 118 M Single 45 Own 4 Management Low
## 119 M Single 53 Own 4 Skilled High
## 120 F Divorced 23 Own 4 Skilled High
## 121 F Divorced 25 Own 1 Skilled Low
## 122 F Divorced 63 Own 3 Skilled Low
## 123 M Single 34 Own 2 Skilled High
## 124 M Single 24 Own 1 Unemployed High
## 125 M Single 35 Own 4 Skilled High
## 126 M Single 30 Own 3 Skilled High
## 127 M Single 29 Other 3 Skilled Low
## 128 F Divorced 20 Rent 4 Skilled High
## 129 M Single 49 Own 4 Skilled Low
## 130 M Single 56 Rent 4 Unskilled Low
## 131 M Single 48 Rent 4 Skilled Low
## 132 F Divorced 24 Own 2 Skilled High
## 133 M Single 22 Own 2 Unskilled High
## 134 M Single 30 Own 4 Skilled High
## 135 M Single 39 Own 3 Management High
## 136 M Married 20 Own 2 Unskilled Low
## 137 F Divorced 22 Own 4 Skilled High
## 138 M Married 24 Rent 2 Skilled High
## 139 M Divorced 41 Own 1 Skilled Low
## 140 M Single 32 Own 4 Skilled Low
## 141 F Divorced 23 Own 2 Skilled High
## 142 F Divorced 41 Rent 3 Skilled Low
## 143 M Single 52 Other 4 Management High
## 144 M Single 65 Own 3 Unskilled High
## 145 F Divorced 26 Own 2 Skilled Low
## 146 M Divorced 33 Own 1 Unskilled High
## 147 F Divorced 56 Own 4 Unskilled Low
## 148 F Divorced 24 Own 4 Unskilled High
## 149 F Divorced 20 Rent 3 Skilled High
## 150 M Single 35 Own 3 Skilled Low
## 151 M Single 34 Own 3 Skilled Low
## 152 M Single 38 Own 4 Management Low
## 153 M Single 34 Own 4 Management Low
## 154 M Single 37 Own 3 Skilled Low
## 155 M Single 31 Other 2 Management Low
## 156 M Single 67 Rent 4 Skilled High
## 157 M Single 26 Own 2 Skilled Low
## 158 F Divorced 24 Own 2 Management High
## 159 M Single 21 Other 1 Skilled Low
## 160 M Married 46 Own 3 Unskilled High
## 161 M Single 22 Rent 4 Skilled High
## 162 F Divorced 20 Rent 4 Skilled Low
## 163 M Divorced 60 Rent 2 Unskilled High
## 164 M Single 25 Own 3 Skilled Low
## 165 F Divorced 21 Rent 4 Skilled High
## 166 F Divorced 22 Own 1 Skilled Low
## 167 M Single 29 Own 2 Management Low
## 168 M Single 56 Own 4 Unskilled High
## 169 M Single 32 Rent 1 Unskilled High
## 170 M Divorced 30 Own 2 Unskilled Low
## 171 M Married 27 Rent 4 Management High
## 172 F Divorced 37 Own 2 Unemployed Low
## 173 M Single 39 Own 4 Unskilled Low
## 174 M Married 26 Own 2 Unemployed Low
## 175 M Divorced 32 Own 2 Skilled Low
## 176 M Single 31 Own 2 Skilled Low
## 177 M Single 35 Own 2 Skilled Low
## 178 M Single 31 Own 3 Management Low
## 179 M Single 64 Own 4 Skilled Low
## 180 M Divorced 27 Own 1 Skilled High
## 181 F Divorced 31 Own 2 Unskilled High
## 182 M Married 32 Own 3 Unskilled High
## 183 M Single 73 Own 4 Unskilled Low
## 184 F Divorced 30 Own 4 Unskilled Low
## 185 M Married 42 Own 1 Unskilled High
## 186 M Single 45 Own 4 Skilled Low
## 187 M Single 27 Own 4 Skilled Low
## 188 F Divorced 22 Rent 4 Unskilled High
## 189 M Single 26 Own 2 Skilled Low
## 190 M Single 33 Own 3 Skilled Low
## 191 F Divorced 27 Own 3 Skilled High
## 192 F Divorced 24 Rent 4 Skilled High
## 193 M Married 21 Own 1 Skilled Low
## 194 F Divorced 28 Rent 4 Unemployed High
## 195 M Single 51 Own 1 Management High
## 196 F Divorced 21 Own 1 Skilled High
## 197 M Single 27 Own 2 Skilled Low
## 198 M Single 40 Own 2 Unskilled High
## 199 M Single 34 Other 4 Skilled Low
## 200 F Divorced 34 Own 1 Unskilled Low
## 201 M Single 63 Own 4 Unskilled Low
## 202 M Single 33 Own 2 Management High
## 203 F Divorced 28 Own 4 Skilled High
## 204 F Divorced 24 Own 2 Skilled High
## 205 F Divorced 18 Rent 4 Unskilled Low
## 206 F Divorced 63 Own 4 Skilled Low
## 207 M Divorced 37 Own 2 Skilled High
## 208 M Single 38 Own 3 Management High
## 209 M Married 22 Rent 1 Skilled High
## 210 F Divorced 31 Own 1 Unskilled High
## 211 M Single 31 Own 2 Skilled Low
## 212 M Single 42 Other 2 Skilled High
## 213 M Single 24 Rent 2 Unskilled High
## 214 M Single 65 Own 4 Management High
## 215 M Single 22 Rent 4 Skilled Low
## 216 F Divorced 22 Rent 2 Unemployed Low
## 217 M Single 51 Own 4 Skilled Low
## 218 F Divorced 23 Own 4 Unskilled High
## 219 F Divorced 30 Own 3 Skilled Low
## 220 M Married 32 Own 2 Skilled High
## 221 F Divorced 21 Own 3 Skilled High
## 222 F Divorced 52 Own 4 Skilled High
## 223 F Divorced 22 Rent 4 Skilled High
## 224 M Single 41 Own 2 Skilled Low
## 225 F Divorced 53 Rent 2 Skilled Low
## 226 F Divorced 54 Other 4 Unemployed High
## 227 M Single 37 Own 3 Unskilled Low
## 228 M Single 27 Own 4 Skilled High
## 229 F Divorced 25 Own 2 Skilled High
## 230 F Divorced 34 Own 2 Skilled Low
## 231 M Divorced 29 Own 2 Management High
## 232 M Single 27 Own 3 Unskilled High
## 233 F Divorced 32 Own 3 Unskilled High
## 234 M Single 29 Own 2 Management Low
## 235 M Single 32 Own 1 Unskilled High
## 236 F Divorced 28 Rent 2 Unskilled High
## 237 F Divorced 25 Rent 4 Unskilled Low
## 238 F Divorced 51 Other 4 Management Low
## 239 M Single 44 Own 2 Management Low
## 240 M Single 33 Own 1 Skilled Low
## 241 F Divorced 22 Rent 3 Unskilled Low
## 242 M Single 35 Own 4 Management Low
## 243 M Single 30 Own 2 Skilled Low
## 244 M Married 27 Own 3 Unskilled Low
## 245 F Divorced 23 Rent 4 Skilled High
## 246 F Divorced 19 Rent 4 Skilled High
## 247 M Single 44 Own 4 Unskilled Low
## 248 M Single 41 Own 1 Unskilled Low
## 249 F Divorced 35 Own 2 Skilled Low
## 250 F Divorced 25 Rent 1 Unemployed High
## 251 M Single 28 Other 2 Management Low
## 252 M Single 34 Own 2 Skilled Low
## 253 F Divorced 31 Own 1 Skilled Low
## 254 M Divorced 32 Rent 1 Skilled High
## 255 M Single 41 Own 2 Skilled High
## 256 M Single 22 Own 2 Skilled High
## 257 M Single 28 Own 3 Management High
## 258 F Divorced 21 Rent 4 Skilled Low
## 259 M Single 41 Own 4 Management High
## 260 M Single 36 Own 2 Unskilled High
## 261 M Single 26 Own 2 Skilled High
## 262 M Single 37 Other 4 Management Low
## 263 M Single 35 Rent 4 Management Low
## 264 M Single 34 Own 1 Skilled Low
## 265 M Single 43 Other 2 Skilled High
## 266 F Divorced 30 Own 2 Management Low
## 267 M Single 31 Rent 3 Skilled Low
## 268 M Single 43 Other 4 Skilled Low
## 269 F Divorced 24 Own 2 Skilled Low
## 270 M Single 26 Own 2 Skilled High
## 271 F Divorced 45 Rent 1 Skilled Low
## 272 M Single 26 Own 3 Unskilled Low
## 273 F Divorced 48 Own 1 Skilled Low
## 274 M Single 43 Own 3 Skilled High
## 275 F Divorced 59 Other 4 Management High
## 276 F Divorced 55 Own 2 Skilled Low
## 277 M Single 29 Own 2 Management High
## 278 F Divorced 32 Own 2 Skilled High
## 279 M Single 53 Own 3 Management High
## 280 M Single 33 Own 2 Unskilled Low
## 281 F Divorced 56 Other 4 Unskilled Low
## 282 M Single 33 Other 4 Skilled Low
## 283 M Single 46 Other 4 Skilled High
## 284 M Single 54 Other 2 Management Low
## 285 F Divorced 22 Own 2 Management Low
## 286 M Single 35 Rent 2 Skilled Low
## 287 M Single 46 Own 4 Unskilled High
## 288 F Divorced 29 Own 3 Management High
## 289 F Divorced 22 Rent 4 Skilled High
## 290 M Married 53 Own 4 Skilled Low
## 291 M Divorced 42 Own 3 Skilled High
## 292 M Married 20 Rent 4 Skilled High
## 293 F Divorced 35 Own 3 Skilled Low
## 294 F Divorced 33 Own 3 Management High
## 295 M Married 26 Own 2 Skilled Low
## 296 M Single 46 Other 4 Skilled Low
## 297 F Divorced 28 Own 2 Skilled High
## 298 M Single 38 Own 4 Skilled Low
## 299 M Single 35 Own 2 Skilled High
## 300 M Single 47 Own 4 Skilled High
## 301 M Single 23 Own 3 Skilled Low
## 302 M Single 56 Other 4 Skilled High
## 303 F Divorced 28 Rent 4 Unskilled High
## 304 M Single 48 Own 3 Skilled Low
## 305 M Single 27 Own 2 Skilled Low
## 306 M Married 23 Own 2 Skilled High
## 307 F Divorced 24 Rent 4 Skilled High
## 308 F Divorced 22 Own 2 Skilled Low
## 309 M Single 42 Rent 4 Skilled High
## 310 M Single 25 Own 2 Skilled High
## 311 F Divorced 47 Other 4 Unskilled High
## 312 F Divorced 32 Rent 4 Skilled High
## 313 M Single 25 Rent 3 Skilled Low
## 314 M Single 36 Own 2 Skilled Low
## 315 M Single 25 Own 2 Skilled High
## 316 M Married 26 Own 2 Skilled Low
## 317 F Divorced 53 Own 4 Unemployed Low
## 318 F Divorced 66 Own 4 Skilled Low
## 319 F Divorced 23 Own 2 Skilled Low
## 320 M Single 25 Own 2 Skilled Low
## 321 M Single 24 Own 2 Unskilled High
## 322 M Single 31 Other 4 Unskilled High
## 323 F Divorced 57 Other 4 Unskilled High
## 324 M Divorced 44 Own 4 Management High
## 325 M Divorced 42 Own 3 Management Low
## 326 F Divorced 27 Rent 4 Skilled High
## 327 M Single 51 Own 4 Skilled Low
## 328 M Single 23 Other 4 Skilled High
## 329 M Single 31 Own 2 Skilled High
## 330 F Divorced 22 Rent 4 Skilled High
## 331 M Single 35 Own 4 Skilled Low
## 332 M Single 37 Other 4 Skilled Low
## 333 M Single 35 Own 1 Management Low
## 334 M Single 30 Own 2 Skilled High
## 335 M Single 49 Other 4 Skilled High
## 336 F Divorced 32 Own 2 Skilled Low
## 337 M Single 52 Own 4 Skilled Low
## 338 M Single 45 Own 2 Skilled High
## 339 M Married 23 Own 1 Skilled Low
## 340 M Single 41 Own 4 Skilled Low
## 341 F Divorced 28 Own 2 Skilled High
## 342 M Single 30 Own 4 Skilled High
## 343 M Single 50 Own 2 Skilled Low
## 344 F Divorced 58 Rent 3 Skilled High
## 345 M Single 36 Own 3 Skilled Low
## 346 M Single 23 Rent 4 Unskilled High
## 347 M Single 48 Own 4 Unskilled Low
## 348 M Single 37 Own 4 Skilled Low
## 349 M Single 20 Rent 4 Skilled High
## 350 F Divorced 23 Own 2 Skilled High
## 351 F Divorced 39 Own 4 Skilled Low
## 352 M Single 34 Other 4 Unskilled Low
## 353 F Divorced 22 Own 4 Skilled Low
## 354 M Single 21 Own 2 Skilled High
## 355 M Single 38 Rent 2 Management High
## 356 M Single 36 Other 4 Skilled Low
## 357 M Single 26 Own 4 Unskilled Low
## 358 M Single 47 Own 4 Skilled Low
## 359 M Single 38 Other 4 Skilled High
## 360 M Single 27 Rent 2 Skilled High
## 361 M Single 25 Own 1 Skilled Low
## 362 M Single 28 Own 3 Skilled Low
## 363 M Single 67 Own 4 Management High
## 364 M Married 25 Own 2 Skilled Low
## 365 M Married 34 Own 1 Skilled Low
## 366 M Single 38 Other 4 Skilled High
## 367 M Single 41 Other 4 Management High
## 368 M Single 26 Own 4 Skilled High
## 369 M Single 35 Own 4 Skilled Low
## 370 M Single 45 Other 4 Skilled High
## 371 F Divorced 32 Own 2 Skilled Low
## 372 M Divorced 47 Other 4 Skilled Low
## 373 M Married 24 Own 3 Unskilled High
## 374 M Divorced 30 Own 4 Unskilled High
## 375 M Single 33 Own 3 Skilled High
## 376 F Divorced 23 Rent 4 Skilled High
## 377 F Divorced 21 Rent 4 Skilled High
## 378 M Single 36 Other 4 Skilled High
## 379 M Single 30 Own 2 Management Low
## 380 M Single 52 Other 4 Skilled High
## 381 M Married 27 Own 2 Skilled High
## 382 F Divorced 44 Own 1 Skilled Low
## 383 M Single 26 Own 2 Skilled Low
## 384 M Single 24 Own 1 Skilled Low
## 385 F Divorced 24 Own 2 Skilled High
## 386 M Single 50 Own 2 Skilled Low
## 387 M Married 31 Own 2 Unskilled Low
## 388 F Divorced 38 Own 4 Skilled High
## 389 M Single 28 Own 3 Skilled High
## 390 M Single 48 Own 3 Unskilled Low
## 391 M Single 56 Other 2 Management High
## 392 F Divorced 31 Own 4 Skilled High
## 393 F Divorced 28 Own 2 Skilled Low
## 394 M Single 26 Own 3 Skilled High
## 395 F Divorced 25 Rent 4 Unskilled High
## 396 F Divorced 41 Other 4 Management High
## 397 F Divorced 24 Rent 4 Skilled Low
## 398 M Single 29 Own 2 Skilled Low
## 399 M Single 25 Own 2 Skilled High
## 400 M Single 35 Own 3 Skilled Low
## 401 M Single 35 Own 2 Unskilled Low
## 402 M Single 26 Own 3 Unskilled Low
## 403 M Single 29 Own 4 Management Low
## 404 M Single 59 Own 4 Unskilled High
## 405 F Divorced 34 Other 4 Skilled High
## 406 M Single 41 Other 4 Skilled Low
## 407 M Divorced 35 Own 3 Skilled High
## 408 M Single 27 Rent 4 Skilled Low
## 409 M Single 41 Own 3 Skilled High
## 410 F Divorced 30 Rent 4 Skilled Low
## 411 M Married 27 Own 2 Management High
## 412 F Divorced 65 Own 3 Unskilled Low
## 413 F Divorced 19 Rent 4 Skilled High
## 414 F Divorced 33 Own 4 Skilled High
## 415 F Divorced 24 Rent 3 Skilled High
## 416 M Married 40 Rent 4 Skilled Low
## 417 M Single 62 Own 4 Skilled Low
## 418 F Divorced 33 Other 4 Unskilled High
## 419 M Married 29 Own 3 Skilled Low
## 420 F Divorced 22 Own 2 Unskilled High
## 421 M Single 35 Other 4 Skilled Low
## 422 M Single 30 Own 4 Skilled High
## 423 F Divorced 28 Own 2 Skilled High
## 424 F Divorced 28 Own 2 Skilled High
## 425 M Single 44 Own 3 Management Lowhead(mydata)## Loan.Purpose Checking Savings Months.Customer Months.Employed Gender
## 1 Small Appliance 0 739 13 12 M
## 2 Furniture 0 1230 25 0 M
## 3 New Car 0 389 19 119 M
## 4 Furniture 638 347 13 14 M
## 5 Education 963 4754 40 45 M
## 6 Furniture 2827 0 11 13 M
## Marital.Status Age Housing Years Job Credit.Risk
## 1 Single 23 Own 3 Unskilled Low
## 2 Divorced 32 Own 1 Skilled High
## 3 Single 38 Own 4 Management High
## 4 Single 36 Own 2 Unskilled High
## 5 Single 31 Rent 3 Skilled Low
## 6 Married 25 Own 1 Skilled Low#Extracting the Savings Column
Saving = mydata$Saving
#Calling the Savings Column
Saving## [1] 739 1230 389 347 4754 0 229 533 493 0 989
## [12] 3305 578 821 228 129 732 683 0 12348 17545 3871
## [23] 0 485 10723 245 0 0 236 485 1708 0 407
## [34] 895 150 490 162 715 323 128 0 109 189 537
## [45] 6520 138 0 660 724 897 947 0 917 595 789
## [56] 0 746 140 659 717 667 0 763 1366 552 14643
## [67] 2665 0 442 8357 0 863 322 800 656 922 885
## [78] 2886 626 0 904 784 806 3281 759 680 104 899
## [89] 1732 706 0 576 904 194 710 5564 192 637 405
## [100] 318 698 369 0 492 308 127 565 12632 116 178
## [111] 901 650 241 609 131 544 10853 0 409 391 322
## [122] 583 12242 479 496 466 1583 1533 0 4873 0 717
## [133] 7876 4449 0 104 897 4033 945 836 325 19568 803
## [144] 10980 265 609 1851 199 500 509 270 457 260 3036
## [155] 643 0 6345 922 909 775 979 948 2790 309 762
## [166] 970 320 861 262 692 540 470 192 12230 772 14186
## [177] 6330 18716 886 750 3870 3273 406 461 340 6490 348
## [188] 506 14717 0 1571 0 411 544 0 835 823 5180
## [199] 408 821 385 2223 0 605 7525 3529 1435 887 243
## [210] 4553 418 771 463 110 10099 13428 208 552 3105 415
## [221] 1238 238 127 0 785 718 493 757 9125 364 598
## [232] 374 0 0 508 956 636 0 1519 922 180 701
## [243] 296 519 800 736 11838 364 212 888 999 0 578
## [254] 136 734 861 855 4486 2017 0 500 859 3305 1218
## [265] 9016 11587 8944 807 867 16804 347 836 142 169 3613
## [276] 403 836 0 11481 3285 164 891 0 841 607 486
## [287] 108 0 113 0 208 603 343 463 0 299 490
## [298] 6628 859 750 954 591 13970 857 5857 3326 726 214
## [309] 207 713 2141 483 127 367 813 0 102 759 0
## [320] 503 823 693 973 648 523 7090 596 904 541 154
## [331] 0 0 337 716 837 0 7710 531 129 941 596
## [342] 987 0 460 0 798 0 959 1482 883 12721 0
## [353] 0 302 538 0 702 2688 0 425 214 0 272
## [364] 124 17124 612 862 146 14190 396 519 0 344 204
## [375] 148 435 914 0 0 412 19811 822 0 3369 0
## [386] 707 818 177 4071 466 460 991 17653 497 4014 921
## [397] 0 0 607 15800 369 4973 0 761 471 674 547
## [408] 524 815 0 989 10406 957 770 950 160 276 137
## [419] 579 2684 0 0 0 712 912#Using the 'mean' function on saving to calculate the saving average
meanSaving = mean(Saving)
#calling the average
head(meanSaving)## [1] 1812.562#computing the standard deviation
spreadSaving = sd(Saving)
#calling the standard deviation of savings
spreadSaving## [1] 3597.285#computing the snr signal to noise ratio of Saving
snr_Saving = meanSaving/spreadSaving
#Calling snr signal
snr_Saving## [1] 0.5038695
The patern tends to be that men are employeed longer than women it almost all age groups. Also, my in thier late 20s to early 40s have a higher employment length than those older or younger. For women in their 20s have a longer employement length than those who are older. The women graph tends to dip in the middle where whomen are between the ages of 30s to mid 50s probably because this is the time woman have kids and tend to spend more time with their kids.
About
This worksheet includes three main tasks in data modeling (a key step to understand the data), basic steps to compute a simple signal-to-noise ratio, and data exploration to identify trends and patterns using Watson Analytics.
Setup
Remember to always set your working directory to the source file location. Go to ‘Session’, scroll down to ‘Set Working Directory’, and click ‘To Source File Location’. Read carefully the below and follow the instructions to complete the tasks and answer any questions. Submit your work to RPubs as detailed in previous notes.
Task 1
To begin the Lab, examine the content of the csv file ‘creditrisk.csv’ by opening the file in RStudio. You can use File -> Import Dataset for that purpose.
Create a simple star relational schema in ERDPlus standalone feature https://erdplus.com/#/standalone, take a screenshot of the image, and upload it below.
Steps to create an star relation schema using erdplus.
From the drop-down option select New Start Schema
Example of how to create an start schema using erdplus
Completed Star schema example
Finally export the diagram as an image.
Insert your answer / ERD plus image in this section.
Task 2
Next, read the csv file into R Studio. It can be useful to name your data to create a shortcut to it. Here we will label the data, ‘mydata’. To see the top head data in the console, one can ‘call’ it using the function ‘head’ and referring to it by its given shortcut name.
mydata = read.csv(file="data/creditrisk.csv")
mydata## Loan.Purpose Checking Savings Months.Customer Months.Employed
## 1 Small Appliance 0 739 13 12
## 2 Furniture 0 1230 25 0
## 3 New Car 0 389 19 119
## 4 Furniture 638 347 13 14
## 5 Education 963 4754 40 45
## 6 Furniture 2827 0 11 13
## 7 New Car 0 229 13 16
## 8 Business 0 533 14 2
## 9 Small Appliance 6509 493 37 9
## 10 Small Appliance 966 0 25 4
## 11 Business 0 989 49 0
## 12 New Car 0 3305 11 15
## 13 Business 322 578 10 14
## 14 New Car 0 821 25 63
## 15 New Car 396 228 13 26
## 16 Used Car 0 129 31 8
## 17 Furniture 652 732 49 4
## 18 New Car 708 683 13 33
## 19 Repairs 207 0 28 116
## 20 Education 287 12348 7 2
## 21 Furniture 0 17545 34 16
## 22 Furniture 101 3871 13 5
## 23 Furniture 0 0 25 23
## 24 Furniture 0 485 37 23
## 25 New Car 0 10723 11 15
## 26 Business 141 245 22 33
## 27 Used Car 0 0 19 58
## 28 Used Car 2484 0 49 46
## 29 Small Appliance 237 236 37 24
## 30 Small Appliance 0 485 19 12
## 31 Education 335 1708 37 7
## 32 Small Appliance 3565 0 31 32
## 33 Small Appliance 0 407 13 2
## 34 Business 16647 895 16 34
## 35 Business 0 150 49 46
## 36 Small Appliance 0 490 5 41
## 37 Furniture 0 162 25 1
## 38 Small Appliance 940 715 9 40
## 39 Small Appliance 0 323 49 42
## 40 New Car 0 128 13 74
## 41 Other 218 0 49 0
## 42 Used Car 0 109 25 26
## 43 Small Appliance 16935 189 37 60
## 44 Furniture 664 537 31 33
## 45 Furniture 150 6520 12 1
## 46 Small Appliance 0 138 7 119
## 47 Furniture 216 0 19 3
## 48 New Car 0 660 17 75
## 49 Business 0 724 25 8
## 50 Small Appliance 0 897 19 5
## 51 Small Appliance 265 947 25 5
## 52 Furniture 4256 0 16 36
## 53 Business 870 917 28 6
## 54 New Car 162 595 22 10
## 55 Used Car 0 789 25 28
## 56 Education 0 0 37 114
## 57 Furniture 0 746 13 16
## 58 New Car 461 140 19 32
## 59 New Car 0 659 19 5
## 60 Furniture 0 717 37 60
## 61 New Car 0 667 29 10
## 62 New Car 580 0 11 8
## 63 Small Appliance 0 763 13 46
## 64 New Car 0 1366 19 17
## 65 Small Appliance 0 552 25 4
## 66 Small Appliance 0 14643 16 115
## 67 Business 758 2665 13 31
## 68 Used Car 399 0 31 0
## 69 Furniture 513 442 7 0
## 70 Furniture 0 8357 25 5
## 71 New Car 0 0 22 9
## 72 Small Appliance 565 863 10 81
## 73 Business 0 322 28 28
## 74 Furniture 0 800 13 69
## 75 Small Appliance 0 656 37 85
## 76 New Car 166 922 13 2
## 77 Business 9783 885 13 3
## 78 Business 674 2886 49 32
## 79 Repairs 0 626 43 0
## 80 Business 15328 0 25 9
## 81 New Car 0 904 12 6
## 82 Education 713 784 61 17
## 83 New Car 0 806 19 3
## 84 Education 0 3281 19 20
## 85 New Car 0 759 16 59
## 86 Small Appliance 0 680 25 3
## 87 Used Car 0 104 37 25
## 88 Small Appliance 303 899 13 3
## 89 Small Appliance 900 1732 37 11
## 90 Furniture 0 706 31 14
## 91 Education 1257 0 10 65
## 92 Small Appliance 0 576 7 14
## 93 Repairs 273 904 7 2
## 94 Business 522 194 25 79
## 95 Small Appliance 0 710 25 1
## 96 Small Appliance 0 5564 25 93
## 97 Small Appliance 0 192 46 13
## 98 New Car 0 637 13 21
## 99 Small Appliance 514 405 49 13
## 100 Furniture 457 318 19 108
## 101 Small Appliance 5133 698 19 14
## 102 New Car 0 369 10 16
## 103 Retraining 644 0 13 88
## 104 Furniture 305 492 19 1
## 105 New Car 9621 308 25 41
## 106 Education 0 127 13 22
## 107 Business 0 565 19 14
## 108 Furniture 0 12632 16 9
## 109 New Car 0 116 49 45
## 110 Used Car 0 178 13 89
## 111 Small Appliance 6851 901 13 21
## 112 Furniture 13496 650 19 20
## 113 Business 509 241 25 14
## 114 Used Car 0 609 37 6
## 115 Furniture 19155 131 25 24
## 116 Furniture 0 544 19 15
## 117 Small Appliance 0 10853 25 81
## 118 Used Car 374 0 25 14
## 119 Large Appliance 0 409 49 15
## 120 Furniture 828 391 9 12
## 121 Furniture 0 322 13 9
## 122 Small Appliance 829 583 7 18
## 123 Small Appliance 0 12242 25 53
## 124 Furniture 0 479 19 0
## 125 New Car 939 496 19 56
## 126 New Car 0 466 25 42
## 127 New Car 889 1583 37 79
## 128 Furniture 876 1533 31 21
## 129 Small Appliance 893 0 16 94
## 130 Business 12760 4873 13 73
## 131 Furniture 0 0 13 94
## 132 Small Appliance 0 717 22 10
## 133 Small Appliance 959 7876 28 20
## 134 Small Appliance 0 4449 25 87
## 135 Other 0 0 25 54
## 136 Business 0 104 25 23
## 137 Repairs 0 897 19 2
## 138 New Car 698 4033 16 20
## 139 Furniture 0 945 13 6
## 140 Furniture 0 836 25 99
## 141 Small Appliance 0 325 19 13
## 142 Small Appliance 12974 19568 13 7
## 143 Furniture 0 803 13 89
## 144 Small Appliance 317 10980 13 17
## 145 Business 0 265 13 10
## 146 Repairs 0 609 31 3
## 147 Small Appliance 0 1851 12 0
## 148 Furniture 192 199 25 5
## 149 New Car 0 500 28 7
## 150 New Car 0 509 16 3
## 151 Used Car 0 270 25 25
## 152 New Car 0 457 13 63
## 153 Used Car 0 260 25 78
## 154 New Car 942 3036 25 36
## 155 Small Appliance 0 643 19 6
## 156 New Car 3329 0 19 15
## 157 Used Car 0 6345 25 19
## 158 Education 0 922 37 9
## 159 Furniture 0 909 25 3
## 160 Large Appliance 0 775 19 8
## 161 Furniture 0 979 25 48
## 162 Furniture 0 948 19 2
## 163 Business 339 2790 22 55
## 164 Used Car 0 309 49 37
## 165 Small Appliance 0 762 10 1
## 166 Small Appliance 0 970 13 14
## 167 Used Car 105 320 28 54
## 168 Small Appliance 0 861 13 111
## 169 Repairs 216 262 37 2
## 170 Furniture 113 692 11 14
## 171 Used Car 109 540 37 1
## 172 New Car 0 470 13 0
## 173 New Car 0 192 7 2
## 174 New Car 8176 12230 7 5
## 175 Repairs 0 772 25 19
## 176 Furniture 468 14186 22 24
## 177 Used Car 7885 6330 16 14
## 178 Small Appliance 0 18716 19 93
## 179 New Car 0 886 22 96
## 180 Business 0 750 37 2
## 181 Small Appliance 0 3870 25 11
## 182 Small Appliance 0 3273 13 4
## 183 Business 0 406 6 35
## 184 Furniture 0 461 13 48
## 185 Furniture 0 340 19 4
## 186 Small Appliance 0 6490 19 85
## 187 Small Appliance 734 348 7 100
## 188 Furniture 0 506 25 3
## 189 Used Car 0 14717 28 7
## 190 Business 172 0 25 36
## 191 New Car 644 1571 19 1
## 192 New Car 0 0 25 19
## 193 Furniture 617 411 31 3
## 194 New Car 0 544 25 0
## 195 Small Appliance 586 0 13 0
## 196 Furniture 0 835 19 42
## 197 Small Appliance 0 823 25 47
## 198 Business 0 5180 22 4
## 199 Small Appliance 0 408 16 12
## 200 New Car 0 821 48 5
## 201 Education 522 385 10 66
## 202 New Car 585 2223 16 0
## 203 New Car 5588 0 22 10
## 204 New Car 0 605 37 20
## 205 Furniture 352 7525 13 4
## 206 Small Appliance 0 3529 14 0
## 207 Business 2715 1435 49 14
## 208 Other 560 887 25 20
## 209 Small Appliance 895 243 13 4
## 210 New Car 305 4553 7 2
## 211 Small Appliance 0 418 19 4
## 212 New Car 0 771 25 0
## 213 Furniture 0 463 11 13
## 214 Business 8948 110 31 90
## 215 Used Car 0 10099 16 108
## 216 Used Car 0 13428 7 0
## 217 Small Appliance 0 208 13 23
## 218 Small Appliance 0 552 13 15
## 219 Education 0 3105 16 19
## 220 Small Appliance 483 415 19 6
## 221 Large Appliance 0 1238 13 0
## 222 Education 0 238 13 2
## 223 Furniture 0 127 31 35
## 224 Business 663 0 19 57
## 225 New Car 624 785 37 9
## 226 Repairs 0 718 19 0
## 227 Furniture 0 493 13 21
## 228 Small Appliance 152 757 49 45
## 229 New Car 0 9125 13 24
## 230 Small Appliance 0 364 13 12
## 231 Business 498 598 37 14
## 232 New Car 0 374 10 19
## 233 Small Appliance 156 0 13 58
## 234 Used Car 1336 0 37 11
## 235 New Car 0 508 13 3
## 236 Small Appliance 0 956 25 4
## 237 Furniture 0 636 22 41
## 238 New Car 2641 0 13 71
## 239 Used Car 0 1519 40 74
## 240 Business 0 922 19 29
## 241 Furniture 0 180 5 2
## 242 Used Car 0 701 22 108
## 243 Small Appliance 0 296 16 8
## 244 Small Appliance 887 519 7 42
## 245 Business 0 800 49 2
## 246 Furniture 0 736 13 6
## 247 Small Appliance 0 11838 7 70
## 248 Small Appliance 0 364 5 35
## 249 New Car 18408 212 13 9
## 250 New Car 497 888 16 3
## 251 Used Car 0 999 25 0
## 252 Small Appliance 946 0 16 83
## 253 Business 986 578 28 1
## 254 Education 8122 136 22 4
## 255 Furniture 0 734 37 111
## 256 Business 778 861 49 21
## 257 Other 645 855 25 17
## 258 Furniture 0 4486 10 3
## 259 New Car 682 2017 37 85
## 260 New Car 19812 0 25 37
## 261 Business 0 500 25 1
## 262 Used Car 0 859 31 89
## 263 Business 859 3305 25 26
## 264 Small Appliance 0 1218 13 38
## 265 New Car 0 9016 49 22
## 266 New Car 0 11587 22 46
## 267 Furniture 0 8944 25 66
## 268 Repairs 0 807 25 75
## 269 Small Appliance 0 867 31 27
## 270 Small Appliance 795 16804 49 40
## 271 Furniture 0 347 16 5
## 272 Furniture 0 836 16 4
## 273 Furniture 0 142 7 53
## 274 Furniture 0 169 19 6
## 275 Other 852 3613 61 83
## 276 Education 0 403 7 5
## 277 Small Appliance 0 836 25 0
## 278 New Car 425 0 19 7
## 279 Business 0 11481 25 18
## 280 Business 0 3285 7 21
## 281 Education 0 164 13 65
## 282 New Car 11072 891 61 17
## 283 Used Car 0 0 37 49
## 284 Used Car 219 841 43 0
## 285 New Car 8060 607 19 71
## 286 New Car 0 486 12 22
## 287 New Car 0 108 25 52
## 288 Small Appliance 0 0 43 28
## 289 New Car 0 113 25 31
## 290 New Car 1613 0 25 118
## 291 Furniture 757 208 25 36
## 292 Retraining 0 603 13 35
## 293 New Car 0 343 19 22
## 294 Education 977 463 10 61
## 295 Education 197 0 37 17
## 296 Furniture 0 299 19 11
## 297 New Car 0 490 13 15
## 298 Small Appliance 0 6628 37 65
## 299 Business 0 859 19 23
## 300 New Car 0 750 13 14
## 301 Small Appliance 256 954 10 13
## 302 New Car 296 591 37 103
## 303 Furniture 0 13970 13 24
## 304 New Car 0 857 11 34
## 305 Furniture 0 5857 19 20
## 306 Small Appliance 298 3326 73 15
## 307 Small Appliance 0 726 19 7
## 308 Furniture 8636 214 11 3
## 309 New Car 0 207 13 119
## 310 New Car 0 713 13 29
## 311 New Car 19766 2141 11 54
## 312 New Car 0 483 19 90
## 313 New Car 0 127 7 13
## 314 Furniture 0 367 37 22
## 315 Small Appliance 0 813 43 28
## 316 Furniture 4089 0 7 14
## 317 New Car 0 102 7 0
## 318 Repairs 271 759 19 0
## 319 New Car 949 0 49 36
## 320 Small Appliance 0 503 13 62
## 321 Small Appliance 911 823 46 4
## 322 New Car 0 693 19 28
## 323 Used Car 0 973 49 81
## 324 New Car 0 648 15 57
## 325 Other 0 523 37 0
## 326 Used Car 271 7090 25 2
## 327 Small Appliance 0 596 13 67
## 328 Used Car 0 904 49 119
## 329 New Car 0 541 19 13
## 330 Furniture 0 154 37 2
## 331 New Car 4802 0 37 12
## 332 Business 177 0 49 9
## 333 Small Appliance 0 337 25 107
## 334 New Car 0 716 19 33
## 335 Education 996 837 49 83
## 336 Education 705 0 25 24
## 337 Furniture 0 7710 25 114
## 338 New Car 0 531 13 5
## 339 Small Appliance 5960 129 13 16
## 340 Furniture 0 941 13 111
## 341 Furniture 759 596 10 18
## 342 Furniture 0 987 37 101
## 343 Small Appliance 651 0 37 102
## 344 Business 257 460 49 75
## 345 Small Appliance 955 0 49 29
## 346 Small Appliance 0 798 25 42
## 347 Small Appliance 8249 0 31 77
## 348 Small Appliance 0 959 11 21
## 349 Small Appliance 956 1482 46 19
## 350 New Car 382 883 31 20
## 351 Furniture 0 12721 37 31
## 352 Education 842 0 37 9
## 353 Repairs 3111 0 13 27
## 354 Small Appliance 0 302 10 30
## 355 Furniture 0 538 25 59
## 356 Small Appliance 2846 0 13 14
## 357 Small Appliance 231 702 10 99
## 358 Repairs 0 2688 10 89
## 359 Small Appliance 17366 0 16 21
## 360 Small Appliance 0 425 13 10
## 361 New Car 332 214 25 2
## 362 Small Appliance 242 0 19 6
## 363 New Car 0 272 7 90
## 364 Business 929 124 9 1
## 365 Small Appliance 0 17124 13 95
## 366 Used Car 0 612 49 32
## 367 New Car 0 862 49 62
## 368 Furniture 0 146 25 46
## 369 New Car 0 14190 37 92
## 370 Used Car 0 396 49 73
## 371 Small Appliance 0 519 31 23
## 372 Used Car 646 0 25 9
## 373 New Car 538 344 13 40
## 374 Furniture 0 204 31 5
## 375 Small Appliance 0 148 43 2
## 376 Furniture 0 435 19 16
## 377 Small Appliance 0 914 19 0
## 378 New Car 135 0 37 7
## 379 Used Car 2472 0 37 41
## 380 New Car 0 412 25 22
## 381 New Car 10417 19811 13 27
## 382 Small Appliance 211 822 8 5
## 383 Small Appliance 16630 0 11 47
## 384 Furniture 0 3369 25 17
## 385 Furniture 642 0 13 65
## 386 Small Appliance 0 707 7 26
## 387 Small Appliance 296 818 19 93
## 388 Business 898 177 22 105
## 389 New Car 478 4071 10 40
## 390 New Car 315 466 13 3
## 391 New Car 122 460 37 109
## 392 Furniture 0 991 7 3
## 393 Small Appliance 0 17653 22 4
## 394 Education 0 497 41 24
## 395 Business 670 4014 31 21
## 396 Business 444 921 28 51
## 397 New Car 3880 0 23 37
## 398 Used Car 819 0 13 23
## 399 Used Car 0 607 37 17
## 400 Large Appliance 0 15800 16 40
## 401 Furniture 0 369 7 23
## 402 Business 0 4973 25 17
## 403 Furniture 0 0 40 30
## 404 New Car 0 761 25 92
## 405 Education 0 471 7 52
## 406 Used Car 0 674 37 69
## 407 New Car 0 547 13 40
## 408 Furniture 161 524 13 106
## 409 Furniture 0 815 19 13
## 410 Used Car 0 0 11 4
## 411 New Car 789 989 31 0
## 412 Small Appliance 765 10406 10 24
## 413 Furniture 0 957 19 11
## 414 New Car 0 770 37 3
## 415 Furniture 983 950 13 5
## 416 Used Car 0 160 13 7
## 417 Used Car 0 276 25 91
## 418 Education 798 137 25 25
## 419 New Car 0 579 22 70
## 420 New Car 193 2684 13 5
## 421 Small Appliance 497 0 7 51
## 422 Furniture 0 0 31 53
## 423 New Car 0 0 25 103
## 424 New Car 0 712 16 6
## 425 New Car 0 912 7 39
## Gender Marital.Status Age Housing Years Job Credit.Risk
## 1 M Single 23 Own 3 Unskilled Low
## 2 M Divorced 32 Own 1 Skilled High
## 3 M Single 38 Own 4 Management High
## 4 M Single 36 Own 2 Unskilled High
## 5 M Single 31 Rent 3 Skilled Low
## 6 M Married 25 Own 1 Skilled Low
## 7 M Married 26 Own 3 Unskilled Low
## 8 M Single 27 Own 1 Unskilled Low
## 9 M Single 25 Own 2 Skilled High
## 10 F Divorced 43 Own 1 Skilled High
## 11 M Single 32 Rent 2 Management High
## 12 M Single 34 Rent 2 Unskilled Low
## 13 M Married 26 Own 1 Skilled Low
## 14 M Single 44 Own 1 Skilled High
## 15 M Single 46 Own 3 Unskilled Low
## 16 M Divorced 39 Own 4 Management Low
## 17 F Divorced 25 Own 2 Skilled High
## 18 M Single 31 Own 2 Skilled Low
## 19 M Single 47 Own 4 Skilled Low
## 20 F Divorced 23 Rent 2 Skilled High
## 21 F Divorced 22 Own 4 Skilled High
## 22 F Divorced 26 Rent 4 Skilled High
## 23 M Married 19 Own 4 Skilled High
## 24 F Divorced 27 Own 2 Management High
## 25 M Single 39 Rent 2 Unskilled Low
## 26 M Single 26 Own 3 Skilled Low
## 27 M Single 50 Other 4 Skilled High
## 28 M Single 34 Other 1 Skilled Low
## 29 M Single 23 Rent 4 Skilled Low
## 30 M Single 23 Own 2 Skilled Low
## 31 M Single 46 Other 4 Skilled High
## 32 M Single 35 Own 3 Skilled Low
## 33 F Divorced 28 Own 2 Skilled Low
## 34 M Single 25 Rent 4 Skilled Low
## 35 F Divorced 36 Rent 4 Skilled High
## 36 M Single 41 Own 1 Unskilled Low
## 37 M Divorced 54 Own 1 Skilled High
## 38 F Divorced 43 Own 2 Unskilled Low
## 39 M Married 33 Own 1 Skilled High
## 40 M Single 34 Own 3 Skilled High
## 41 M Single 39 Other 4 Unemployed Low
## 42 M Single 34 Own 3 Unskilled Low
## 43 M Single 30 Own 2 Skilled Low
## 44 M Single 48 Own 2 Skilled High
## 45 F Divorced 19 Own 1 Skilled Low
## 46 M Married 29 Rent 2 Skilled Low
## 47 F Divorced 26 Rent 3 Skilled High
## 48 M Single 42 Rent 4 Skilled High
## 49 M Single 30 Rent 2 Skilled High
## 50 M Married 38 Own 4 Skilled Low
## 51 M Married 21 Own 1 Skilled High
## 52 F Divorced 32 Rent 4 Unskilled Low
## 53 M Single 35 Own 2 Skilled High
## 54 M Divorced 46 Own 4 Skilled Low
## 55 M Single 37 Own 3 Management Low
## 56 M Single 39 Own 4 Management High
## 57 F Divorced 29 Own 3 Skilled Low
## 58 M Single 27 Rent 3 Unskilled Low
## 59 F Divorced 22 Rent 3 Skilled High
## 60 M Single 40 Own 2 Skilled High
## 61 M Single 44 Own 2 Unskilled High
## 62 M Single 26 Own 4 Unskilled High
## 63 F Divorced 57 Own 3 Unskilled Low
## 64 M Single 34 Own 4 Unskilled Low
## 65 M Married 47 Own 4 Skilled High
## 66 M Single 46 Own 3 Skilled Low
## 67 M Single 38 Own 4 Unskilled Low
## 68 F Divorced 52 Own 1 Management High
## 69 M Single 34 Own 1 Management Low
## 70 M Single 29 Other 4 Skilled High
## 71 M Single 39 Own 2 Unskilled High
## 72 M Single 36 Own 4 Unskilled Low
## 73 M Single 25 Own 4 Skilled Low
## 74 M Single 59 Own 3 Skilled High
## 75 M Single 27 Own 2 Skilled Low
## 76 F Divorced 24 Rent 1 Skilled High
## 77 F Divorced 25 Own 1 Unemployed High
## 78 M Single 29 Own 2 Skilled Low
## 79 M Single 64 Own 4 Unemployed Low
## 80 M Single 31 Own 4 Skilled Low
## 81 M Single 38 Own 4 Unskilled Low
## 82 M Single 41 Other 4 Skilled High
## 83 F Divorced 22 Own 2 Unskilled High
## 84 F Divorced 29 Own 2 Skilled High
## 85 M Single 32 Rent 3 Skilled High
## 86 F Divorced 34 Own 4 Skilled High
## 87 M Single 23 Own 4 Skilled High
## 88 M Single 21 Own 1 Skilled High
## 89 F Divorced 49 Other 4 Skilled High
## 90 M Divorced 31 Own 2 Skilled Low
## 91 F Divorced 40 Rent 4 Unskilled Low
## 92 F Divorced 28 Own 1 Skilled Low
## 93 M Married 21 Own 1 Unskilled Low
## 94 M Divorced 30 Own 4 Skilled High
## 95 F Divorced 37 Own 3 Skilled Low
## 96 M Single 33 Own 2 Skilled Low
## 97 M Single 22 Other 4 Skilled High
## 98 F Divorced 23 Own 2 Unskilled High
## 99 F Divorced 21 Own 2 Skilled High
## 100 M Single 40 Own 1 Skilled Low
## 101 M Single 36 Own 2 Skilled High
## 102 M Single 29 Own 1 Skilled Low
## 103 M Single 37 Own 4 Skilled Low
## 104 F Divorced 26 Own 1 Skilled Low
## 105 M Single 37 Other 3 Skilled High
## 106 M Single 39 Rent 4 Unskilled High
## 107 M Married 27 Own 2 Skilled High
## 108 F Divorced 19 Rent 4 Skilled Low
## 109 M Single 45 Other 4 Skilled High
## 110 M Single 34 Other 4 Skilled High
## 111 F Divorced 43 Rent 2 Unskilled Low
## 112 M Single 33 Own 1 Unskilled High
## 113 M Single 35 Own 4 Unskilled High
## 114 M Single 31 Other 2 Management Low
## 115 M Single 25 Own 2 Skilled Low
## 116 F Divorced 27 Own 2 Skilled Low
## 117 F Divorced 56 Rent 4 Management Low
## 118 M Single 45 Own 4 Management Low
## 119 M Single 53 Own 4 Skilled High
## 120 F Divorced 23 Own 4 Skilled High
## 121 F Divorced 25 Own 1 Skilled Low
## 122 F Divorced 63 Own 3 Skilled Low
## 123 M Single 34 Own 2 Skilled High
## 124 M Single 24 Own 1 Unemployed High
## 125 M Single 35 Own 4 Skilled High
## 126 M Single 30 Own 3 Skilled High
## 127 M Single 29 Other 3 Skilled Low
## 128 F Divorced 20 Rent 4 Skilled High
## 129 M Single 49 Own 4 Skilled Low
## 130 M Single 56 Rent 4 Unskilled Low
## 131 M Single 48 Rent 4 Skilled Low
## 132 F Divorced 24 Own 2 Skilled High
## 133 M Single 22 Own 2 Unskilled High
## 134 M Single 30 Own 4 Skilled High
## 135 M Single 39 Own 3 Management High
## 136 M Married 20 Own 2 Unskilled Low
## 137 F Divorced 22 Own 4 Skilled High
## 138 M Married 24 Rent 2 Skilled High
## 139 M Divorced 41 Own 1 Skilled Low
## 140 M Single 32 Own 4 Skilled Low
## 141 F Divorced 23 Own 2 Skilled High
## 142 F Divorced 41 Rent 3 Skilled Low
## 143 M Single 52 Other 4 Management High
## 144 M Single 65 Own 3 Unskilled High
## 145 F Divorced 26 Own 2 Skilled Low
## 146 M Divorced 33 Own 1 Unskilled High
## 147 F Divorced 56 Own 4 Unskilled Low
## 148 F Divorced 24 Own 4 Unskilled High
## 149 F Divorced 20 Rent 3 Skilled High
## 150 M Single 35 Own 3 Skilled Low
## 151 M Single 34 Own 3 Skilled Low
## 152 M Single 38 Own 4 Management Low
## 153 M Single 34 Own 4 Management Low
## 154 M Single 37 Own 3 Skilled Low
## 155 M Single 31 Other 2 Management Low
## 156 M Single 67 Rent 4 Skilled High
## 157 M Single 26 Own 2 Skilled Low
## 158 F Divorced 24 Own 2 Management High
## 159 M Single 21 Other 1 Skilled Low
## 160 M Married 46 Own 3 Unskilled High
## 161 M Single 22 Rent 4 Skilled High
## 162 F Divorced 20 Rent 4 Skilled Low
## 163 M Divorced 60 Rent 2 Unskilled High
## 164 M Single 25 Own 3 Skilled Low
## 165 F Divorced 21 Rent 4 Skilled High
## 166 F Divorced 22 Own 1 Skilled Low
## 167 M Single 29 Own 2 Management Low
## 168 M Single 56 Own 4 Unskilled High
## 169 M Single 32 Rent 1 Unskilled High
## 170 M Divorced 30 Own 2 Unskilled Low
## 171 M Married 27 Rent 4 Management High
## 172 F Divorced 37 Own 2 Unemployed Low
## 173 M Single 39 Own 4 Unskilled Low
## 174 M Married 26 Own 2 Unemployed Low
## 175 M Divorced 32 Own 2 Skilled Low
## 176 M Single 31 Own 2 Skilled Low
## 177 M Single 35 Own 2 Skilled Low
## 178 M Single 31 Own 3 Management Low
## 179 M Single 64 Own 4 Skilled Low
## 180 M Divorced 27 Own 1 Skilled High
## 181 F Divorced 31 Own 2 Unskilled High
## 182 M Married 32 Own 3 Unskilled High
## 183 M Single 73 Own 4 Unskilled Low
## 184 F Divorced 30 Own 4 Unskilled Low
## 185 M Married 42 Own 1 Unskilled High
## 186 M Single 45 Own 4 Skilled Low
## 187 M Single 27 Own 4 Skilled Low
## 188 F Divorced 22 Rent 4 Unskilled High
## 189 M Single 26 Own 2 Skilled Low
## 190 M Single 33 Own 3 Skilled Low
## 191 F Divorced 27 Own 3 Skilled High
## 192 F Divorced 24 Rent 4 Skilled High
## 193 M Married 21 Own 1 Skilled Low
## 194 F Divorced 28 Rent 4 Unemployed High
## 195 M Single 51 Own 1 Management High
## 196 F Divorced 21 Own 1 Skilled High
## 197 M Single 27 Own 2 Skilled Low
## 198 M Single 40 Own 2 Unskilled High
## 199 M Single 34 Other 4 Skilled Low
## 200 F Divorced 34 Own 1 Unskilled Low
## 201 M Single 63 Own 4 Unskilled Low
## 202 M Single 33 Own 2 Management High
## 203 F Divorced 28 Own 4 Skilled High
## 204 F Divorced 24 Own 2 Skilled High
## 205 F Divorced 18 Rent 4 Unskilled Low
## 206 F Divorced 63 Own 4 Skilled Low
## 207 M Divorced 37 Own 2 Skilled High
## 208 M Single 38 Own 3 Management High
## 209 M Married 22 Rent 1 Skilled High
## 210 F Divorced 31 Own 1 Unskilled High
## 211 M Single 31 Own 2 Skilled Low
## 212 M Single 42 Other 2 Skilled High
## 213 M Single 24 Rent 2 Unskilled High
## 214 M Single 65 Own 4 Management High
## 215 M Single 22 Rent 4 Skilled Low
## 216 F Divorced 22 Rent 2 Unemployed Low
## 217 M Single 51 Own 4 Skilled Low
## 218 F Divorced 23 Own 4 Unskilled High
## 219 F Divorced 30 Own 3 Skilled Low
## 220 M Married 32 Own 2 Skilled High
## 221 F Divorced 21 Own 3 Skilled High
## 222 F Divorced 52 Own 4 Skilled High
## 223 F Divorced 22 Rent 4 Skilled High
## 224 M Single 41 Own 2 Skilled Low
## 225 F Divorced 53 Rent 2 Skilled Low
## 226 F Divorced 54 Other 4 Unemployed High
## 227 M Single 37 Own 3 Unskilled Low
## 228 M Single 27 Own 4 Skilled High
## 229 F Divorced 25 Own 2 Skilled High
## 230 F Divorced 34 Own 2 Skilled Low
## 231 M Divorced 29 Own 2 Management High
## 232 M Single 27 Own 3 Unskilled High
## 233 F Divorced 32 Own 3 Unskilled High
## 234 M Single 29 Own 2 Management Low
## 235 M Single 32 Own 1 Unskilled High
## 236 F Divorced 28 Rent 2 Unskilled High
## 237 F Divorced 25 Rent 4 Unskilled Low
## 238 F Divorced 51 Other 4 Management Low
## 239 M Single 44 Own 2 Management Low
## 240 M Single 33 Own 1 Skilled Low
## 241 F Divorced 22 Rent 3 Unskilled Low
## 242 M Single 35 Own 4 Management Low
## 243 M Single 30 Own 2 Skilled Low
## 244 M Married 27 Own 3 Unskilled Low
## 245 F Divorced 23 Rent 4 Skilled High
## 246 F Divorced 19 Rent 4 Skilled High
## 247 M Single 44 Own 4 Unskilled Low
## 248 M Single 41 Own 1 Unskilled Low
## 249 F Divorced 35 Own 2 Skilled Low
## 250 F Divorced 25 Rent 1 Unemployed High
## 251 M Single 28 Other 2 Management Low
## 252 M Single 34 Own 2 Skilled Low
## 253 F Divorced 31 Own 1 Skilled Low
## 254 M Divorced 32 Rent 1 Skilled High
## 255 M Single 41 Own 2 Skilled High
## 256 M Single 22 Own 2 Skilled High
## 257 M Single 28 Own 3 Management High
## 258 F Divorced 21 Rent 4 Skilled Low
## 259 M Single 41 Own 4 Management High
## 260 M Single 36 Own 2 Unskilled High
## 261 M Single 26 Own 2 Skilled High
## 262 M Single 37 Other 4 Management Low
## 263 M Single 35 Rent 4 Management Low
## 264 M Single 34 Own 1 Skilled Low
## 265 M Single 43 Other 2 Skilled High
## 266 F Divorced 30 Own 2 Management Low
## 267 M Single 31 Rent 3 Skilled Low
## 268 M Single 43 Other 4 Skilled Low
## 269 F Divorced 24 Own 2 Skilled Low
## 270 M Single 26 Own 2 Skilled High
## 271 F Divorced 45 Rent 1 Skilled Low
## 272 M Single 26 Own 3 Unskilled Low
## 273 F Divorced 48 Own 1 Skilled Low
## 274 M Single 43 Own 3 Skilled High
## 275 F Divorced 59 Other 4 Management High
## 276 F Divorced 55 Own 2 Skilled Low
## 277 M Single 29 Own 2 Management High
## 278 F Divorced 32 Own 2 Skilled High
## 279 M Single 53 Own 3 Management High
## 280 M Single 33 Own 2 Unskilled Low
## 281 F Divorced 56 Other 4 Unskilled Low
## 282 M Single 33 Other 4 Skilled Low
## 283 M Single 46 Other 4 Skilled High
## 284 M Single 54 Other 2 Management Low
## 285 F Divorced 22 Own 2 Management Low
## 286 M Single 35 Rent 2 Skilled Low
## 287 M Single 46 Own 4 Unskilled High
## 288 F Divorced 29 Own 3 Management High
## 289 F Divorced 22 Rent 4 Skilled High
## 290 M Married 53 Own 4 Skilled Low
## 291 M Divorced 42 Own 3 Skilled High
## 292 M Married 20 Rent 4 Skilled High
## 293 F Divorced 35 Own 3 Skilled Low
## 294 F Divorced 33 Own 3 Management High
## 295 M Married 26 Own 2 Skilled Low
## 296 M Single 46 Other 4 Skilled Low
## 297 F Divorced 28 Own 2 Skilled High
## 298 M Single 38 Own 4 Skilled Low
## 299 M Single 35 Own 2 Skilled High
## 300 M Single 47 Own 4 Skilled High
## 301 M Single 23 Own 3 Skilled Low
## 302 M Single 56 Other 4 Skilled High
## 303 F Divorced 28 Rent 4 Unskilled High
## 304 M Single 48 Own 3 Skilled Low
## 305 M Single 27 Own 2 Skilled Low
## 306 M Married 23 Own 2 Skilled High
## 307 F Divorced 24 Rent 4 Skilled High
## 308 F Divorced 22 Own 2 Skilled Low
## 309 M Single 42 Rent 4 Skilled High
## 310 M Single 25 Own 2 Skilled High
## 311 F Divorced 47 Other 4 Unskilled High
## 312 F Divorced 32 Rent 4 Skilled High
## 313 M Single 25 Rent 3 Skilled Low
## 314 M Single 36 Own 2 Skilled Low
## 315 M Single 25 Own 2 Skilled High
## 316 M Married 26 Own 2 Skilled Low
## 317 F Divorced 53 Own 4 Unemployed Low
## 318 F Divorced 66 Own 4 Skilled Low
## 319 F Divorced 23 Own 2 Skilled Low
## 320 M Single 25 Own 2 Skilled Low
## 321 M Single 24 Own 2 Unskilled High
## 322 M Single 31 Other 4 Unskilled High
## 323 F Divorced 57 Other 4 Unskilled High
## 324 M Divorced 44 Own 4 Management High
## 325 M Divorced 42 Own 3 Management Low
## 326 F Divorced 27 Rent 4 Skilled High
## 327 M Single 51 Own 4 Skilled Low
## 328 M Single 23 Other 4 Skilled High
## 329 M Single 31 Own 2 Skilled High
## 330 F Divorced 22 Rent 4 Skilled High
## 331 M Single 35 Own 4 Skilled Low
## 332 M Single 37 Other 4 Skilled Low
## 333 M Single 35 Own 1 Management Low
## 334 M Single 30 Own 2 Skilled High
## 335 M Single 49 Other 4 Skilled High
## 336 F Divorced 32 Own 2 Skilled Low
## 337 M Single 52 Own 4 Skilled Low
## 338 M Single 45 Own 2 Skilled High
## 339 M Married 23 Own 1 Skilled Low
## 340 M Single 41 Own 4 Skilled Low
## 341 F Divorced 28 Own 2 Skilled High
## 342 M Single 30 Own 4 Skilled High
## 343 M Single 50 Own 2 Skilled Low
## 344 F Divorced 58 Rent 3 Skilled High
## 345 M Single 36 Own 3 Skilled Low
## 346 M Single 23 Rent 4 Unskilled High
## 347 M Single 48 Own 4 Unskilled Low
## 348 M Single 37 Own 4 Skilled Low
## 349 M Single 20 Rent 4 Skilled High
## 350 F Divorced 23 Own 2 Skilled High
## 351 F Divorced 39 Own 4 Skilled Low
## 352 M Single 34 Other 4 Unskilled Low
## 353 F Divorced 22 Own 4 Skilled Low
## 354 M Single 21 Own 2 Skilled High
## 355 M Single 38 Rent 2 Management High
## 356 M Single 36 Other 4 Skilled Low
## 357 M Single 26 Own 4 Unskilled Low
## 358 M Single 47 Own 4 Skilled Low
## 359 M Single 38 Other 4 Skilled High
## 360 M Single 27 Rent 2 Skilled High
## 361 M Single 25 Own 1 Skilled Low
## 362 M Single 28 Own 3 Skilled Low
## 363 M Single 67 Own 4 Management High
## 364 M Married 25 Own 2 Skilled Low
## 365 M Married 34 Own 1 Skilled Low
## 366 M Single 38 Other 4 Skilled High
## 367 M Single 41 Other 4 Management High
## 368 M Single 26 Own 4 Skilled High
## 369 M Single 35 Own 4 Skilled Low
## 370 M Single 45 Other 4 Skilled High
## 371 F Divorced 32 Own 2 Skilled Low
## 372 M Divorced 47 Other 4 Skilled Low
## 373 M Married 24 Own 3 Unskilled High
## 374 M Divorced 30 Own 4 Unskilled High
## 375 M Single 33 Own 3 Skilled High
## 376 F Divorced 23 Rent 4 Skilled High
## 377 F Divorced 21 Rent 4 Skilled High
## 378 M Single 36 Other 4 Skilled High
## 379 M Single 30 Own 2 Management Low
## 380 M Single 52 Other 4 Skilled High
## 381 M Married 27 Own 2 Skilled High
## 382 F Divorced 44 Own 1 Skilled Low
## 383 M Single 26 Own 2 Skilled Low
## 384 M Single 24 Own 1 Skilled Low
## 385 F Divorced 24 Own 2 Skilled High
## 386 M Single 50 Own 2 Skilled Low
## 387 M Married 31 Own 2 Unskilled Low
## 388 F Divorced 38 Own 4 Skilled High
## 389 M Single 28 Own 3 Skilled High
## 390 M Single 48 Own 3 Unskilled Low
## 391 M Single 56 Other 2 Management High
## 392 F Divorced 31 Own 4 Skilled High
## 393 F Divorced 28 Own 2 Skilled Low
## 394 M Single 26 Own 3 Skilled High
## 395 F Divorced 25 Rent 4 Unskilled High
## 396 F Divorced 41 Other 4 Management High
## 397 F Divorced 24 Rent 4 Skilled Low
## 398 M Single 29 Own 2 Skilled Low
## 399 M Single 25 Own 2 Skilled High
## 400 M Single 35 Own 3 Skilled Low
## 401 M Single 35 Own 2 Unskilled Low
## 402 M Single 26 Own 3 Unskilled Low
## 403 M Single 29 Own 4 Management Low
## 404 M Single 59 Own 4 Unskilled High
## 405 F Divorced 34 Other 4 Skilled High
## 406 M Single 41 Other 4 Skilled Low
## 407 M Divorced 35 Own 3 Skilled High
## 408 M Single 27 Rent 4 Skilled Low
## 409 M Single 41 Own 3 Skilled High
## 410 F Divorced 30 Rent 4 Skilled Low
## 411 M Married 27 Own 2 Management High
## 412 F Divorced 65 Own 3 Unskilled Low
## 413 F Divorced 19 Rent 4 Skilled High
## 414 F Divorced 33 Own 4 Skilled High
## 415 F Divorced 24 Rent 3 Skilled High
## 416 M Married 40 Rent 4 Skilled Low
## 417 M Single 62 Own 4 Skilled Low
## 418 F Divorced 33 Other 4 Unskilled High
## 419 M Married 29 Own 3 Skilled Low
## 420 F Divorced 22 Own 2 Unskilled High
## 421 M Single 35 Other 4 Skilled Low
## 422 M Single 30 Own 4 Skilled High
## 423 F Divorced 28 Own 2 Skilled High
## 424 F Divorced 28 Own 2 Skilled High
## 425 M Single 44 Own 3 Management Lowhead(mydata)## Loan.Purpose Checking Savings Months.Customer Months.Employed Gender
## 1 Small Appliance 0 739 13 12 M
## 2 Furniture 0 1230 25 0 M
## 3 New Car 0 389 19 119 M
## 4 Furniture 638 347 13 14 M
## 5 Education 963 4754 40 45 M
## 6 Furniture 2827 0 11 13 M
## Marital.Status Age Housing Years Job Credit.Risk
## 1 Single 23 Own 3 Unskilled Low
## 2 Divorced 32 Own 1 Skilled High
## 3 Single 38 Own 4 Management High
## 4 Single 36 Own 2 Unskilled High
## 5 Single 31 Rent 3 Skilled Low
## 6 Married 25 Own 1 Skilled LowTo capture, or extract, the checking and savings columns and perform some analytics on them, we must first be able to extract the columns from the data separately. Using the ‘$’ sign following the label for the data extracts a specific column. For convenience, we relabel the extracted data.
Below, we have extracted the checking column.
#Extracting the Checking Column
checking = mydata$Checking
#Calling the Checking Column to display top head values
head(checking)## [1] 0 0 0 638 963 2827Now, fill in the code to extract and call the savings column.
#Go ahead and extract the Savings Column?
#Call the Savings Column to display top head values?In order to calculate the mean, or the average by hand of the checkings columns, one can add each individual entry and divide by the total number or rows. This would take much time, but thankfully, R has a command for this.
We have done an example using the checkings column. Compute the same using the savings column.
#Using the 'mean' function on checking to calculate the checking average and naming the average 'meanChecking'
meanChecking = mean(checking)
#Calling the average
meanChecking## [1] 1048.014#Find the average of the savings column and name the average of the savings meanSavings?
#Call meanSavings?Next, compute the standard deviation or spread of both the checkings and savings columns.
#Computing the standard deviation of standard deviation
spreadChecking = sd(checking)
#Find the standard deviation of savings?Now, to compute the SNR, the signal to noise ratio, a formula is created because there is no built in function.
SNR is the mean, or average, divided by the spread.
#Compute the snr signal to noise ratio of Checking and name it snr_Checking
snr_Checking = meanChecking/spreadChecking
#Call snr_Checking
snr_Checking## [1] 0.3330006#Find the snr of the savings and name it snr_Saving?
#Call snr_Saving?Task 3
Login to Watson Analytics and upload the file creditrisk.csv to your account. Use Explore to find patterns in the data. Consider trend of ‘Months Employed over Age by Gender’. Save your work and upload any screenshot(s) here. Refer to Task 1 on how to upload a photo. For every uploaded screenshot share your observations on general data trends and data behavior. Any screenshot without observations will be dismissed.