Split (1)

train · 10k rows

RowNumber int64	CustomerId int64	Surname string	CreditScore int64	Geography string	Gender string	Age int64	Tenure int64	Balance float64	NumOfProducts int64	HasCrCard int64	IsActiveMember int64	EstimatedSalary float64	Exited int64
4,101	15,693,322	Shaver	635	Germany	Female	37	9	146,748.07	1	0	1	11,407.58	0
4,102	15,589,544	Wallis	673	Spain	Female	57	4	0	2	1	1	49,684.09	0
4,103	15,772,030	Coupp	662	Spain	Male	33	3	0	2	0	1	68,064.83	0
4,104	15,693,337	Perry	683	Spain	Male	41	0	148,863.17	1	1	1	163,911.32	0
4,105	15,676,571	Bezrukova	850	France	Male	55	6	0	1	1	0	944.41	1
4,106	15,701,392	Lucciano	815	Spain	Male	28	6	0	2	0	1	185,547.71	0
4,107	15,741,092	Ingram	671	Spain	Male	34	10	153,360.02	1	1	0	140,509.86	0
4,108	15,643,865	Lo Duca	601	France	Female	40	3	92,055.36	1	0	1	164,652.02	1
4,109	15,769,389	Wan	709	Germany	Female	39	9	124,723.92	1	1	0	73,641.86	0
4,110	15,807,768	Cohn	702	Germany	Male	28	1	103,033.83	1	1	1	40,321.87	0
4,111	15,801,630	Yen	558	France	Male	40	6	0	2	1	0	173,844.89	0
4,112	15,705,034	Peng	691	Spain	Male	40	1	0	2	1	1	145,613.17	0
4,113	15,763,107	Little	700	France	Female	30	9	0	1	1	1	174,971.64	0
4,114	15,667,085	Meng	667	France	Male	33	4	0	2	1	1	131,834.75	0
4,115	15,647,008	Adams	624	Germany	Male	54	3	116,726.22	1	1	0	110,498.1	1
4,116	15,584,505	Hill	580	France	Female	23	5	113,923.81	2	0	0	196,241.43	0
4,117	15,748,068	Boyle	571	Spain	Female	31	3	0	2	1	1	194,667.92	0
4,118	15,663,964	Pagnotto	561	France	Male	37	5	0	2	1	0	83,093.25	0
4,119	15,782,311	Feng	529	France	Male	28	9	0	2	1	1	52,545.24	0
4,120	15,588,197	Endrizzi	670	France	Male	36	7	0	2	0	0	59,571.5	0
4,121	15,610,105	Shen	666	Germany	Female	21	1	121,827.43	2	1	1	99,818.31	0
4,122	15,606,133	Lay	628	Spain	Male	42	7	0	2	0	1	172,967.87	0
4,123	15,599,403	Wu	577	France	Male	60	10	125,389.7	2	1	1	178,616.73	0
4,124	15,648,225	Shephard	652	Spain	Female	38	1	103,895.31	1	0	1	159,649.44	0
4,125	15,608,406	Schmidt	678	France	Male	26	5	111,128.04	1	1	0	60,941.27	1
4,126	15,633,378	Davidson	692	Spain	Female	49	9	0	2	1	0	178,342.63	0
4,127	15,664,759	Lamb	675	Spain	Male	32	10	0	2	1	0	191,545.65	0
4,128	15,625,545	Hussey	712	Spain	Male	52	9	0	1	1	1	117,977.45	1
4,129	15,772,148	Ferrari	639	Germany	Female	37	5	151,242.48	1	0	1	49,637.65	0
4,130	15,810,829	Macfarlan	618	France	Male	48	7	0	1	1	0	13,921.82	1
4,131	15,731,669	Szabados	554	France	Male	39	2	129,709.62	1	1	0	173,197.12	0
4,132	15,738,634	Yuan	533	France	Male	47	9	83,347.25	1	1	1	137,696.25	0
4,133	15,737,571	Matveyev	540	Spain	Female	28	6	84,121.04	1	0	1	80,698.54	0
4,134	15,667,602	Cheng	704	Spain	Male	33	3	0	2	1	0	73,018.74	0
4,135	15,684,147	Palerma	678	France	Male	43	5	102,338.19	1	1	1	79,649.62	0
4,136	15,789,874	Wang	712	France	Female	29	3	87,375.78	2	0	0	166,194.53	0
4,137	15,757,952	Teng	651	France	Male	44	2	0	3	1	0	102,530.35	1
4,138	15,698,732	K'ung	789	Germany	Male	51	3	104,677.09	1	1	0	74,265.38	0
4,139	15,714,355	Sinclair	775	Germany	Male	32	8	121,669.23	1	0	1	125,898.39	0
4,140	15,599,090	McKelvey	564	Germany	Male	40	7	108,407.34	1	1	1	83,681.2	0
4,141	15,762,048	Yuan	841	Germany	Female	33	7	154,969.79	2	1	1	99,505.75	0
4,142	15,790,596	Moran	850	Spain	Male	39	0	141,829.67	1	1	1	92,748.16	0
4,143	15,609,623	McConnell	637	France	Female	63	5	0	1	1	0	28,092.77	1
4,144	15,711,901	Iheatu	500	France	Male	45	2	109,162.82	1	1	1	126,145.08	0
4,145	15,779,809	Giordano	655	France	Male	44	8	87,471.63	1	0	1	188,593.98	0
4,146	15,729,018	Alexander	666	France	Female	33	2	147,229.65	1	1	1	56,410.17	0
4,147	15,698,246	Gordon	658	France	Female	24	2	0	2	1	1	84,694.49	0
4,148	15,712,409	Tang	749	Germany	Male	66	6	182,532.23	2	1	1	195,429.92	0
4,149	15,758,306	T'an	654	France	Male	32	6	0	2	1	1	137,898.57	0
4,150	15,621,435	Davies	623	France	Female	39	1	160,903.2	1	0	0	78,774.36	0
4,151	15,566,295	Sanders	761	France	Female	33	6	138,053.79	2	1	0	148,779.41	0
4,152	15,569,098	Winifred	627	France	Male	44	6	153,548.12	1	0	0	35,300.08	1
4,153	15,662,532	Holmes	757	Germany	Male	31	8	149,085.9	2	1	1	197,077.36	0
4,154	15,664,001	Riddle	695	Germany	Female	53	8	95,231.91	1	0	0	70,140.8	1
4,155	15,703,437	Chinedum	726	France	Male	34	3	0	2	1	0	196,288.46	0
4,156	15,708,003	Aleksandrova	587	Spain	Male	41	8	85,109.21	1	1	0	1,557.82	0
4,157	15,599,452	Conti	605	Germany	Female	43	8	125,338.8	2	1	0	23,970.13	0
4,158	15,719,793	Watson	850	Spain	Male	62	5	0	2	1	1	180,243.56	0
4,159	15,771,580	Davison	850	France	Female	38	0	106,831.69	1	0	1	148,977.72	0
4,160	15,732,268	Cook	751	France	Male	29	3	159,597.45	1	1	0	39,934.41	0
4,161	15,722,350	Udinesi	627	Germany	Female	37	7	147,361.57	1	1	1	133,031.96	0
4,162	15,611,371	Siciliani	736	France	Male	43	4	176,134.54	1	1	1	52,856.88	0
4,163	15,673,584	Bell	652	France	Female	74	5	0	2	1	1	937.15	0
4,164	15,636,396	Jackson	627	France	Female	35	7	0	2	0	1	193,022.44	0
4,165	15,706,170	Onyemere	636	France	Male	34	1	84,055.43	1	0	0	37,490.84	0
4,166	15,725,478	McClemans	775	France	Male	60	7	0	2	1	1	111,558.7	0
4,167	15,654,562	Ma	850	Spain	Female	45	5	174,088.3	4	1	0	5,669.31	1
4,168	15,737,509	Morrison	850	Spain	Male	34	8	199,229.14	1	0	0	68,106.29	0
4,169	15,690,796	Chambers	516	France	Male	37	8	0	1	1	0	101,834.58	0
4,170	15,716,728	Basedow	513	Spain	Female	42	10	0	2	0	1	73,151.25	0
4,171	15,605,665	Nwora	673	Germany	Female	69	3	78,833.15	2	1	1	37,196.15	0
4,172	15,748,481	Howey	564	France	Female	27	6	0	1	0	0	7,819.76	0
4,173	15,757,777	Pai	636	France	Female	35	2	0	2	1	1	23,129.46	0
4,174	15,747,808	Ni	712	France	Male	29	3	102,540.61	1	1	1	189,680.79	0
4,175	15,810,593	Forbes	568	France	Male	51	4	0	3	1	1	66,586.56	0
4,176	15,693,376	Baryshnikov	741	Spain	Male	43	0	0	2	1	1	2,920.63	1
4,177	15,579,808	Kramer	754	Germany	Female	39	8	129,401.87	1	1	1	87,684.93	0
4,178	15,598,275	Sochima	709	France	Female	32	7	0	2	1	1	199,418.02	0
4,179	15,737,080	Marchesi	510	France	Female	32	1	0	2	0	1	28,515.17	0
4,180	15,668,580	Todd	716	Spain	Male	33	2	0	2	1	1	92,916.53	0
4,181	15,569,438	Mai	607	Germany	Male	36	10	106,702.94	2	0	0	198,313.69	0
4,182	15,675,842	Pinto	656	Spain	Male	26	4	139,584.57	1	1	0	36,308.93	0
4,183	15,577,587	Reynolds	550	Germany	Male	52	5	121,016.23	1	1	1	41,730.37	1
4,184	15,625,592	Sal	486	France	Male	26	2	0	2	1	1	31,399.4	0
4,185	15,635,141	Miller	598	Germany	Male	59	8	118,210.42	2	0	0	60,192.14	1
4,186	15,642,570	Scott	675	Spain	Male	35	8	0	2	1	0	29,062.25	0
4,187	15,702,175	Herrin	755	France	Female	29	4	148,654.84	2	1	1	28,805.09	0
4,188	15,677,785	Stevenson	656	Spain	Male	32	5	136,963.12	1	1	0	133,814.28	0
4,189	15,786,153	McKenzie	644	Germany	Male	47	9	137,774.11	2	1	0	151,902.78	0
4,190	15,759,499	Gardiner	598	France	Female	32	4	111,156.52	1	1	1	167,376.26	0
4,191	15,659,568	Atkinson	850	Spain	Female	31	3	121,237.65	1	1	1	31,022.56	0
4,192	15,715,597	Onyemauchechi	679	France	Male	36	1	97,234.58	1	1	0	188,997.08	0
4,193	15,610,147	Ross	632	France	Male	60	2	0	2	0	1	2,085.32	0
4,194	15,802,362	Newland	550	Spain	Male	45	0	0	2	0	1	70,399.71	0
4,195	15,660,524	Hu	572	Germany	Female	54	9	97,382.53	1	1	1	195,771.95	0
4,196	15,747,168	Sanders	626	Germany	Female	47	2	103,108.8	1	0	1	166,475.44	1
4,197	15,796,910	Tsui	625	Spain	Female	57	7	0	1	0	0	84,106.17	1
4,198	15,707,674	Marino	515	France	Female	58	2	131,852.81	1	1	0	81,436.68	1
4,199	15,565,706	Akobundu	612	Spain	Male	35	1	0	1	1	1	83,256.26	1
4,200	15,587,596	Morrison	628	Spain	Female	39	8	107,553.33	1	1	0	117,523.41	0

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.