Datasets:
moaminsharifi
/
Churn_Modelling

Dataset card Data Studio Files
xet
Community
1
RowNumber
int64
1
10k
CustomerId
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15.6M
15.8M
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850
Geography
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Gender
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Age
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92
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10
Balance
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0
251k
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EstimatedSalary
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200k
Exited
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1
9,401
15,584,897
Kuo
639
France
Female
31
3
98,360.03
1
0
0
20,973.8
0
9,402
15,601,857
Woodhouse
705
Germany
Female
46
4
115,518.07
1
0
0
76,544.9
1
9,403
15,674,156
Tretiakova
810
Germany
Male
69
3
27,288.43
1
1
1
110,509.9
0
9,404
15,695,465
Gibson
638
France
Female
36
6
0
1
1
0
164,247.51
0
9,405
15,792,232
Moss
595
Spain
Female
43
5
0
2
0
0
105,149.8
0
9,406
15,807,900
Chineze
575
France
Male
36
7
0
1
1
1
55,868.97
1
9,407
15,743,760
Davidson
850
France
Male
31
6
131,996.66
2
1
1
178,747.43
0
9,408
15,652,835
Liang
419
Spain
Female
27
2
121,580.42
1
0
1
134,720.51
0
9,409
15,767,818
Graham
640
France
Male
55
10
132,436.34
1
1
0
978.66
0
9,410
15,591,150
Nwebube
570
Spain
Male
34
10
0
2
0
1
183,387.12
0
9,411
15,734,659
Sozonov
640
Germany
Female
46
5
107,978.4
2
1
0
155,876.06
0
9,412
15,796,115
Forbes
689
Germany
Female
40
4
78,119.59
4
1
0
119,259.34
1
9,413
15,724,648
Chikezie
725
France
Male
26
6
98,684.15
1
0
0
133,720.57
0
9,414
15,737,732
Onwuemelie
751
France
Female
44
10
0
2
1
0
170,634.49
0
9,415
15,632,280
Toth
544
Spain
Female
53
9
0
1
1
0
125,692.07
1
9,416
15,750,407
Hunt
768
Germany
Female
43
2
129,264.05
2
0
0
19,150.14
0
9,417
15,795,370
Mazure
648
Germany
Male
37
6
131,753.41
1
1
0
86,894.67
0
9,418
15,656,829
Hughes
577
Spain
Female
33
6
0
2
1
0
57,975.8
0
9,419
15,643,794
Bennett
639
Spain
Female
27
2
0
1
1
1
82,938.99
0
9,420
15,798,605
Tien
686
Germany
Male
26
1
57,422.62
1
1
1
79,189.4
0
9,421
15,637,324
Kay
657
France
Female
28
7
0
2
0
1
5,177.62
0
9,422
15,589,589
Bryan
613
France
Male
34
5
144,094.2
1
1
0
44,510.26
0
9,423
15,778,936
Ingamells
701
France
Male
33
9
147,510.34
1
1
0
190,611.92
0
9,424
15,757,385
Milne
578
Spain
Female
28
8
161,592.76
1
1
0
177,834.79
0
9,425
15,666,200
Lombardo
689
France
Female
40
1
0
2
1
1
119,446.64
0
9,426
15,683,977
Owens
687
Spain
Female
72
4
0
2
1
1
50,267.69
0
9,427
15,675,518
Charlton
499
Spain
Female
53
1
75,225.53
2
0
0
144,849.1
1
9,428
15,584,812
Overby
693
Spain
Female
39
0
0
2
0
0
81,901.6
0
9,429
15,752,984
Chifley
737
France
Female
70
9
87,542.89
2
1
1
42,576.86
0
9,430
15,577,913
Oliver
651
France
Female
32
8
144,581.96
1
1
1
87,609.5
0
9,431
15,591,980
Hill
753
France
Male
33
5
122,568.05
2
1
1
82,820.85
0
9,432
15,598,948
DeRose
523
Spain
Female
24
5
172,231.93
1
0
1
155,144.12
0
9,433
15,574,142
Chuang
458
Germany
Female
28
2
171,932.26
2
1
1
9,578.24
0
9,434
15,582,903
Edwards
643
France
Male
39
7
0
2
1
1
170,392.59
0
9,435
15,733,229
Rodriguez
638
Spain
Female
34
7
0
2
0
0
3,946.29
0
9,436
15,635,752
Lo
685
Germany
Male
38
4
111,798.06
2
1
1
102,184.66
0
9,437
15,771,000
Powell
684
France
Male
38
4
0
3
1
0
75,609.84
0
9,438
15,804,864
Chu
670
France
Female
27
5
79,336.61
1
1
1
26,170.08
0
9,439
15,641,175
Munro
701
Germany
Male
63
3
120,916.52
3
0
0
144,727.45
1
9,440
15,692,226
Onwumelu
705
France
Female
31
3
142,905.51
1
1
1
58,134.97
0
9,441
15,584,156
Siciliani
593
Spain
Male
27
10
0
3
0
0
94,620
1
9,442
15,702,656
Yobachi
651
France
Female
33
1
96,834.78
1
1
0
108,764.69
0
9,443
15,606,552
Akabueze
741
France
Male
37
9
105,261.76
2
1
1
149,503.54
0
9,444
15,687,001
Chiemenam
596
Germany
Male
54
1
123,544
1
1
1
120,314.75
1
9,445
15,781,903
Odinakachukwu
581
Germany
Male
41
2
127,913.71
2
1
1
44,205.95
0
9,446
15,731,951
Reilly
689
Spain
Female
28
5
95,328.6
1
1
0
6,129.61
1
9,447
15,580,953
Forbes
544
France
Male
30
4
73,218.89
1
0
1
126,796.69
0
9,448
15,810,390
Amadi
718
France
Female
41
1
0
2
0
1
27,509.52
1
9,449
15,628,274
Ferri
583
Germany
Male
35
8
149,995.72
2
1
0
42,143.55
0
9,450
15,615,444
Y?an
663
Germany
Male
28
8
123,674.28
2
1
1
87,985.2
0
9,451
15,784,010
Williamson
666
Germany
Male
33
2
124,125.26
1
1
0
81,884.8
0
9,452
15,571,586
Briggs
524
Spain
Male
29
3
159,035.45
1
1
0
2,705.31
1
9,453
15,748,616
Napolitani
599
France
Male
27
5
0
2
1
0
30,546.4
0
9,454
15,769,402
Carpenter
667
France
Male
27
7
156,811.74
1
1
1
149,402.59
0
9,455
15,739,248
Lin
727
France
Male
52
4
0
2
1
1
118,429.02
0
9,456
15,603,481
Robinson
689
Spain
Female
55
4
0
2
1
1
58,442.25
0
9,457
15,723,604
Collins
639
France
Male
39
6
150,555.83
1
1
0
30,414.17
0
9,458
15,797,822
Kingsley
678
France
Male
28
2
109,137.12
1
1
1
58,814.41
0
9,459
15,665,064
Harvey
523
France
Male
36
8
158,351.02
2
1
0
155,304.53
0
9,460
15,640,580
Obiora
650
France
Female
47
9
0
1
1
0
187,943.6
0
9,461
15,581,089
Knight
744
Spain
Male
35
7
0
2
1
1
43,036.6
0
9,462
15,728,605
Hung
697
France
Male
40
4
0
2
0
1
26,543.28
0
9,463
15,737,385
Curtis
800
Spain
Female
46
6
0
2
1
0
171,928.04
0
9,464
15,714,789
Perez
664
France
Male
24
7
0
1
0
1
35,611.35
0
9,465
15,786,035
Gosnell
740
France
Male
39
9
0
2
1
0
19,047.23
0
9,466
15,815,259
Fang
835
France
Female
56
2
0
2
1
1
39,820.13
0
9,467
15,592,716
Clarke
559
France
Male
52
2
0
1
1
0
129,013.59
1
9,468
15,734,850
Milanesi
676
Spain
Male
36
1
82,729.49
1
1
0
113,810.12
0
9,469
15,638,047
Chia
613
Germany
Female
45
9
142,765.24
2
1
0
34,749.65
0
9,470
15,674,573
Gearhart
713
France
Female
25
4
121,172.97
1
1
1
56,268.98
0
9,471
15,694,859
McLean
751
Germany
Female
28
10
132,932.14
2
1
1
46,630.47
0
9,472
15,776,404
Williamson
523
France
Male
22
8
123,374.46
1
1
1
124,906.59
0
9,473
15,579,345
Murphy
775
Germany
Female
74
0
161,371.5
1
1
1
134,869.93
0
9,474
15,690,733
Angelo
608
Spain
Male
45
4
0
2
0
0
36,697.48
1
9,475
15,631,481
Thomson
673
France
Male
51
8
79,563.36
2
1
1
172,200.91
0
9,476
15,620,988
Murray
616
France
Male
46
2
0
2
1
0
137,136.46
0
9,477
15,571,529
Kirby
650
Germany
Female
48
7
138,232.24
1
1
0
57,594.78
0
9,478
15,592,104
Lane
655
France
Female
41
5
0
1
0
0
36,548
1
9,479
15,651,900
Bergamaschi
782
Germany
Female
53
1
81,571.05
1
1
0
182,960.46
1
9,480
15,596,212
Yang
781
Spain
Male
35
1
0
2
0
0
42,117.9
0
9,481
15,710,687
Mills
593
France
Female
33
0
95,927.04
1
1
0
199,478.05
0
9,482
15,613,787
Chidubem
505
Spain
Male
35
8
116,932.59
1
1
0
91,092.84
0
9,483
15,599,211
Findlay
707
France
Male
40
1
0
2
1
0
14,090.4
1
9,484
15,675,983
Wood
692
France
Female
36
3
79,551.12
1
0
1
178,267.07
0
9,485
15,622,370
Boyle
813
Germany
Male
30
1
116,416.94
1
0
1
85,808.22
0
9,486
15,656,319
Toscano
850
Spain
Male
37
4
88,141.1
1
1
0
109,659.12
0
9,487
15,605,130
Seccombe
753
France
Male
32
6
177,729.13
1
1
1
161,642.08
0
9,488
15,672,574
Uspenskaya
850
Spain
Female
32
5
0
1
1
1
3,830.59
0
9,489
15,659,355
McKenzie
671
Spain
Male
32
6
123,912.78
2
1
1
146,636.44
0
9,490
15,777,907
Liang
791
France
Female
33
3
0
1
1
1
144,413.92
1
9,491
15,655,171
Yermakova
624
France
Male
80
3
0
1
1
1
65,801.44
0
9,492
15,619,674
White
649
France
Female
35
4
108,306.44
1
1
1
192,486.24
0
9,493
15,775,192
Rounsevell
732
Germany
Female
48
4
102,962.62
1
1
0
120,852.85
1
9,494
15,617,657
Ts'ai
664
France
Female
36
0
103,502.22
1
1
1
146,191.82
0
9,495
15,688,951
Stoneman
789
Germany
Male
43
8
119,654.44
2
0
1
148,412.24
1
9,496
15,763,460
Yao
680
France
Male
33
10
183,768.47
1
1
0
164,119.35
0
9,497
15,756,992
Chukwukere
701
France
Male
37
1
0
2
1
0
163,457.55
0
9,498
15,617,454
Ifeatu
684
France
Female
25
1
0
2
0
1
144,978.47
0
9,499
15,701,932
Millar
586
France
Female
52
6
140,900.97
1
1
1
67,288.89
0
9,500
15,700,813
Igwebuike
522
Germany
Female
25
5
94,049.92
2
1
0
103,269
0