Datasets:

moaminsharifi
/

Churn_Modelling

RowNumber int64 1 10k	CustomerId int64 15.6M 15.8M	Surname stringlengths 2 23	CreditScore int64 350 850	Geography stringclasses 3 values	Gender stringclasses 2 values	Age int64 18 92	Tenure int64 0 10	Balance float64 0 251k	NumOfProducts int64 1 4	HasCrCard int64 0 1	IsActiveMember int64 0 1	EstimatedSalary float64 11.6 200k	Exited int64 0 1
1	15,634,602	Hargrave	619	France	Female	42	2	0	1	1	1	101,348.88	1
2	15,647,311	Hill	608	Spain	Female	41	1	83,807.86	1	0	1	112,542.58	0
3	15,619,304	Onio	502	France	Female	42	8	159,660.8	3	1	0	113,931.57	1
4	15,701,354	Boni	699	France	Female	39	1	0	2	0	0	93,826.63	0
5	15,737,888	Mitchell	850	Spain	Female	43	2	125,510.82	1	1	1	79,084.1	0
6	15,574,012	Chu	645	Spain	Male	44	8	113,755.78	2	1	0	149,756.71	1
7	15,592,531	Bartlett	822	France	Male	50	7	0	2	1	1	10,062.8	0
8	15,656,148	Obinna	376	Germany	Female	29	4	115,046.74	4	1	0	119,346.88	1
9	15,792,365	He	501	France	Male	44	4	142,051.07	2	0	1	74,940.5	0
10	15,592,389	H?	684	France	Male	27	2	134,603.88	1	1	1	71,725.73	0
11	15,767,821	Bearce	528	France	Male	31	6	102,016.72	2	0	0	80,181.12	0
12	15,737,173	Andrews	497	Spain	Male	24	3	0	2	1	0	76,390.01	0
13	15,632,264	Kay	476	France	Female	34	10	0	2	1	0	26,260.98	0
14	15,691,483	Chin	549	France	Female	25	5	0	2	0	0	190,857.79	0
15	15,600,882	Scott	635	Spain	Female	35	7	0	2	1	1	65,951.65	0
16	15,643,966	Goforth	616	Germany	Male	45	3	143,129.41	2	0	1	64,327.26	0
17	15,737,452	Romeo	653	Germany	Male	58	1	132,602.88	1	1	0	5,097.67	1
18	15,788,218	Henderson	549	Spain	Female	24	9	0	2	1	1	14,406.41	0
19	15,661,507	Muldrow	587	Spain	Male	45	6	0	1	0	0	158,684.81	0
20	15,568,982	Hao	726	France	Female	24	6	0	2	1	1	54,724.03	0
21	15,577,657	McDonald	732	France	Male	41	8	0	2	1	1	170,886.17	0
22	15,597,945	Dellucci	636	Spain	Female	32	8	0	2	1	0	138,555.46	0
23	15,699,309	Gerasimov	510	Spain	Female	38	4	0	1	1	0	118,913.53	1
24	15,725,737	Mosman	669	France	Male	46	3	0	2	0	1	8,487.75	0
25	15,625,047	Yen	846	France	Female	38	5	0	1	1	1	187,616.16	0
26	15,738,191	Maclean	577	France	Male	25	3	0	2	0	1	124,508.29	0
27	15,736,816	Young	756	Germany	Male	36	2	136,815.64	1	1	1	170,041.95	0
28	15,700,772	Nebechi	571	France	Male	44	9	0	2	0	0	38,433.35	0
29	15,728,693	McWilliams	574	Germany	Female	43	3	141,349.43	1	1	1	100,187.43	0
30	15,656,300	Lucciano	411	France	Male	29	0	59,697.17	2	1	1	53,483.21	0
31	15,589,475	Azikiwe	591	Spain	Female	39	3	0	3	1	0	140,469.38	1
32	15,706,552	Odinakachukwu	533	France	Male	36	7	85,311.7	1	0	1	156,731.91	0
33	15,750,181	Sanderson	553	Germany	Male	41	9	110,112.54	2	0	0	81,898.81	0
34	15,659,428	Maggard	520	Spain	Female	42	6	0	2	1	1	34,410.55	0
35	15,732,963	Clements	722	Spain	Female	29	9	0	2	1	1	142,033.07	0
36	15,794,171	Lombardo	475	France	Female	45	0	134,264.04	1	1	0	27,822.99	1
37	15,788,448	Watson	490	Spain	Male	31	3	145,260.23	1	0	1	114,066.77	0
38	15,729,599	Lorenzo	804	Spain	Male	33	7	76,548.6	1	0	1	98,453.45	0
39	15,717,426	Armstrong	850	France	Male	36	7	0	1	1	1	40,812.9	0
40	15,585,768	Cameron	582	Germany	Male	41	6	70,349.48	2	0	1	178,074.04	0
41	15,619,360	Hsiao	472	Spain	Male	40	4	0	1	1	0	70,154.22	0
42	15,738,148	Clarke	465	France	Female	51	8	122,522.32	1	0	0	181,297.65	1
43	15,687,946	Osborne	556	France	Female	61	2	117,419.35	1	1	1	94,153.83	0
44	15,755,196	Lavine	834	France	Female	49	2	131,394.56	1	0	0	194,365.76	1
45	15,684,171	Bianchi	660	Spain	Female	61	5	155,931.11	1	1	1	158,338.39	0
46	15,754,849	Tyler	776	Germany	Female	32	4	109,421.13	2	1	1	126,517.46	0
47	15,602,280	Martin	829	Germany	Female	27	9	112,045.67	1	1	1	119,708.21	1
48	15,771,573	Okagbue	637	Germany	Female	39	9	137,843.8	1	1	1	117,622.8	1
49	15,766,205	Yin	550	Germany	Male	38	2	103,391.38	1	0	1	90,878.13	0
50	15,771,873	Buccho	776	Germany	Female	37	2	103,769.22	2	1	0	194,099.12	0
51	15,616,550	Chidiebele	698	Germany	Male	44	10	116,363.37	2	1	0	198,059.16	0
52	15,768,193	Trevisani	585	Germany	Male	36	5	146,050.97	2	0	0	86,424.57	0
53	15,683,553	O'Brien	788	France	Female	33	5	0	2	0	0	116,978.19	0
54	15,702,298	Parkhill	655	Germany	Male	41	8	125,561.97	1	0	0	164,040.94	1
55	15,569,590	Yoo	601	Germany	Male	42	1	98,495.72	1	1	0	40,014.76	1
56	15,760,861	Phillipps	619	France	Male	43	1	125,211.92	1	1	1	113,410.49	0
57	15,630,053	Tsao	656	France	Male	45	5	127,864.4	1	1	0	87,107.57	0
58	15,647,091	Endrizzi	725	Germany	Male	19	0	75,888.2	1	0	0	45,613.75	0
59	15,623,944	T'ien	511	Spain	Female	66	4	0	1	1	0	1,643.11	1
60	15,804,771	Velazquez	614	France	Male	51	4	40,685.92	1	1	1	46,775.28	0
61	15,651,280	Hunter	742	Germany	Male	35	5	136,857	1	0	0	84,509.57	0
62	15,773,469	Clark	687	Germany	Female	27	9	152,328.88	2	0	0	126,494.82	0
63	15,702,014	Jeffrey	555	Spain	Male	33	1	56,084.69	2	0	0	178,798.13	0
64	15,751,208	Pirozzi	684	Spain	Male	56	8	78,707.16	1	1	1	99,398.36	0
65	15,592,461	Jackson	603	Germany	Male	26	4	109,166.37	1	1	1	92,840.67	0
66	15,789,484	Hammond	751	Germany	Female	36	6	169,831.46	2	1	1	27,758.36	0
67	15,696,061	Brownless	581	Germany	Female	34	1	101,633.04	1	1	0	110,431.51	0
68	15,641,582	Chibugo	735	Germany	Male	43	10	123,180.01	2	1	1	196,673.28	0
69	15,638,424	Glauert	661	Germany	Female	35	5	150,725.53	2	0	1	113,656.85	0
70	15,755,648	Pisano	675	France	Female	21	8	98,373.26	1	1	0	18,203	0
71	15,703,793	Konovalova	738	Germany	Male	58	2	133,745.44	4	1	0	28,373.86	1
72	15,620,344	McKee	813	France	Male	29	6	0	1	1	0	33,953.87	0
73	15,812,518	Palermo	657	Spain	Female	37	0	163,607.18	1	0	1	44,203.55	0
74	15,779,052	Ballard	604	Germany	Female	25	5	157,780.84	2	1	1	58,426.81	0
75	15,770,811	Wallace	519	France	Male	36	9	0	2	0	1	145,562.4	0
76	15,780,961	Cavenagh	735	France	Female	21	1	178,718.19	2	1	0	22,388	0
77	15,614,049	Hu	664	France	Male	55	8	0	2	1	1	139,161.64	0
78	15,662,085	Read	678	France	Female	32	9	0	1	1	1	148,210.64	0
79	15,575,185	Bushell	757	Spain	Male	33	5	77,253.22	1	0	1	194,239.63	0
80	15,803,136	Postle	416	Germany	Female	41	10	122,189.66	2	1	0	98,301.61	0
81	15,706,021	Buley	665	France	Female	34	1	96,645.54	2	0	0	171,413.66	0
82	15,663,706	Leonard	777	France	Female	32	2	0	1	1	0	136,458.19	1
83	15,641,732	Mills	543	France	Female	36	3	0	2	0	0	26,019.59	0
84	15,701,164	Onyeorulu	506	France	Female	34	4	90,307.62	1	1	1	159,235.29	0
85	15,738,751	Beit	493	France	Female	46	4	0	2	1	0	1,907.66	0
86	15,805,254	Ndukaku	652	Spain	Female	75	10	0	2	1	1	114,675.75	0
87	15,762,418	Gant	750	Spain	Male	22	3	121,681.82	1	1	0	128,643.35	1
88	15,625,759	Rowley	729	France	Male	30	9	0	2	1	0	151,869.35	0
89	15,622,897	Sharpe	646	France	Female	46	4	0	3	1	0	93,251.42	1
90	15,767,954	Osborne	635	Germany	Female	28	3	81,623.67	2	1	1	156,791.36	0
91	15,757,535	Heap	647	Spain	Female	44	5	0	3	1	1	174,205.22	1
92	15,731,511	Ritchie	808	France	Male	45	7	118,626.55	2	1	0	147,132.46	0
93	15,809,248	Cole	524	France	Female	36	10	0	2	1	0	109,614.57	0
94	15,640,635	Capon	769	France	Male	29	8	0	2	1	1	172,290.61	0
95	15,676,966	Capon	730	Spain	Male	42	4	0	2	0	1	85,982.47	0
96	15,699,461	Fiorentini	515	Spain	Male	35	10	176,273.95	1	0	1	121,277.78	0
97	15,738,721	Graham	773	Spain	Male	41	9	102,827.44	1	0	1	64,595.25	0
98	15,693,683	Yuille	814	Germany	Male	29	8	97,086.4	2	1	1	197,276.13	0
99	15,604,348	Allard	710	Spain	Male	22	8	0	2	0	0	99,645.04	0
100	15,633,059	Fanucci	413	France	Male	34	9	0	2	0	0	6,534.18	0

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Size of downloaded dataset files:

675 kB

Size of the auto-converted Parquet files:

403 kB

Number of rows:

10,000