Split (1)

train · 46.2k rows

postcode stringclasses 352 values	age int64 16 105 ⌀	sex stringclasses 5 values	licences int64 1 1.39M ⌀
0870	17	Male	1
0870	21	Male	2
0870	22	Female	1
0870	25	Male	1
0870	29	Male	1
0870	30	Female	1
0870	31	Male	1
0870	32	Male	1
0870	37	Male	1
0870	38	Female	1
0870	38	Male	1
0870	41	Male	2
0870	44	Female	1
0870	44	Male	1
0870	47	Male	1
0870	53	Male	1
0870	55	Female	1
0870	63	Female	2
0870	67	Male	1
0871	27	Male	1
0871	28	Female	1
0871	30	Female	2
0871	32	Female	1
0871	33	Male	1
0871	35	Female	1
0871	35	Male	1
0871	41	Male	1
0871	47	Female	1
0871	51	Female	1
0871	51	Male	1
0871	55	Male	1
0871	58	Female	1
0871	58	Male	1
0871	63	Female	1
0871	67	Female	1
0871	69	Female	1
0871	73	Male	1
0872	16	Female	2
0872	16	Male	1
0872	17	Female	3
0872	17	Male	2
0872	18	Female	3
0872	18	Male	3
0872	19	Female	7
0872	19	Male	4
0872	20	Female	6
0872	20	Male	5
0872	21	Female	5
0872	21	Male	7
0872	22	Female	13
0872	22	Male	2
0872	23	Female	7
0872	23	Male	7
0872	24	Female	7
0872	24	Male	5
0872	25	Female	10
0872	25	Male	8
0872	26	Female	5
0872	26	Male	5
0872	27	Female	11
0872	27	Male	9
0872	28	Female	10
0872	28	Male	10
0872	28	Not listed	1
0872	29	Female	11
0872	29	Male	6
0872	30	Female	8
0872	30	Male	5
0872	31	Female	14
0872	31	Male	8
0872	32	Female	10
0872	32	Male	7
0872	33	Female	7
0872	33	Male	8
0872	34	Female	4
0872	34	Male	5
0872	35	Female	6
0872	35	Male	11
0872	36	Female	6
0872	36	Male	7
0872	36	Not listed	1
0872	37	Female	9
0872	37	Male	7
0872	38	Female	10
0872	38	Male	4
0872	39	Female	8
0872	39	Male	3
0872	40	Female	3
0872	40	Male	1
0872	40	Not listed	1
0872	41	Female	3
0872	41	Male	4
0872	42	Female	7
0872	42	Male	1
0872	43	Female	5
0872	43	Male	2
0872	44	Female	8
0872	44	Male	1
0872	45	Female	9
0872	45	Male	1

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