training.python.datascience/source/pandas/data/csv/heights.csv

1	earn	height	sex	ed	age	race
2	50000	74.4244387818035	male	16	45	white
3	60000	65.5375428255647	female	16	58	white
4	30000	63.6291977374349	female	16	29	white
5	50000	63.1085616752971	female	16	91	other
6	51000	63.4024835710879	female	17	39	white
7	9000	64.3995075440034	female	15	26	white
8	29000	61.6563258264214	female	12	49	white
9	32000	72.6985437364783	male	17	46	white
10	2000	72.0394668497611	male	15	21	hispanic
11	27000	72.2349325611722	male	12	26	white
12	6530	69.5121464275289	male	16	65	white
13	30000	68.0316082600038	male	11	34	white
14	12000	67.556933917338	male	12	27	white
15	12000	65.4305870763492	female	12	51	white
16	22000	65.6628545243293	female	16	35	white
17	17000	67.7587687384803	male	12	58	white
18	40000	68.3518425801303	female	14	29	white
19	44000	69.6095718003344	male	13	44	white
20	7000	64.1845656777732	female	12	55	black
21	53000	73.0746091497131	male	13	35	black
22	5000	62.3755270198453	female	13	51	white
23	14000	63.0239301056135	female	14	21	white
24	5500	67.2299039133359	male	14	22	white
25	40000	65.551107801497	female	12	41	white
26	34000	72.0796453857329	male	12	45	white
27	10000	63.0911300827283	female	12	35	black
28	27000	64.3235489164945	female	16	60	white
29	50000	71.6428528276738	male	16	38	white
30	41000	76.7930946839042	male	16	33	white
31	15000	63.8939143288881	female	14	25	white
32	25000	63.8026230719406	female	12	33	white
33	75000	71.5922314410564	male	17	39	white
34	27000	67.5219634829555	male	17	31	white
35	12000	64.3943514756393	female	12	26	white
36	7500	61.1782226648647	female	14	78	white
37	30000	66.9838783009909	female	14	31	black
38	21000	65.3164557656273	female	12	57	white
39	27000	63.5741851450875	female	14	26	white
40	3000	66.6110004822258	female	15	65	white
41	25000	64.9117550808005	female	12	30	white
42	24000	64.7896799838636	female	12	41	white
43	32000	66.937690645922	female	18	29	white
44	10000	68.1728129491676	female	17	30	white
45	11000	60.4506599237211	female	12	21	hispanic
46	18700	64.7932535589207	female	13	32	white
47	20000	61.8149190000258	female	12	29	white
48	3500	71.5721453060396	male	10	18	white
49	13000	67.3144058254547	male	8	56	black
50	25000	69.8998733619228	male	12	65	white
51	21000	69.7617020171601	male	17	41	white
52	34000	67.7464710318018	female	17	49	white
53	6000	60.190221529454	female	12	65	white
54	17000	71.0064998776652	male	12	28	white
55	35000	71.1667981331702	male	12	32	white
56	4000	72.7356298717204	male	13	18	white
57	14000	68.1382231093012	female	14	55	white
58	10000	66.3798112401273	female	12	57	white
59	25000	69.2327845250256	male	16	29	white
60	16000	63.2739377985708	female	14	27	white
61	16000	61.8277627213392	male	14	28	hispanic
62	16500	64.2212092091795	female	14	43	white
63	4000	63.841265113093	female	9	68	white
64	3840	66.9747701257002	female	9	52	white
65	22000	71.451489093015	male	12	39	white
66	200	59.6126462582033	female	16	53	white
67	26000	65.7993855320383	female	16	27	white
68	2500	66.4580405310262	female	15	21	white
69	17000	64.60288038617	female	14	39	white
70	8000	70.4404814683367	female	13	22	white
71	12000	65.922813506797	female	13	68	white
72	10000	61.8568268497474	female	12	47	white
73	10000	65.7844401644543	female	15	67	white
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75	2400	67.0453292939346	female	8	39	hispanic
76	30000	68.3055060780607	male	12	32	hispanic
77	30000	70.0254597608	male	12	33	white
78	10000	61.810385880759	female	12	38	white
79	5000	62.9510710034519	female	13	26	white
80	12000	65.8211369581986	female	13	63	white
81	20000	70.3975481863599	female	10	61	white
82	20000	68.3777844423894	female	12	36	white
83	20000	69.9326998807956	male	14	23	white
84	1200	66.1718059259001	female	12	20	white
85	700	68.4563631031197	female	16	32	white
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87	10000	61.1496579824015	female	12	22	hispanic
88	30000	63.3633463280275	female	12	73	white
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93	18000	67.6827305052429	female	12	66	white
94	16040	64.4967685842421	female	12	33	white
95	15000	66.8124041855335	female	14	30	black
96	10000	68.7464377458673	male	17	23	white
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103	38000	67.5161435012706	female	17	44	white
104	17000	65.6008437511045	female	14	43	hispanic
105	32000	76.800193942152	male	16	30	white
106	27500	67.1053807893768	female	12	58	white
107	16500	62.1516434333753	female	12	44	white
108	25000	66.8676242611837	female	18	35	white
109	27000	61.0422025278676	female	18	43	white
110	5000	64.1232857718132	female	12	28	white
111	70000	61.5448151710443	female	16	38	white
112	5000	62.5562363923527	female	12	40	white
113	5000	68.1637655736413	male	16	24	white
114	20000	63.6551274901722	female	15	26	white
115	4000	72.373517293483	male	15	21	white
116	60000	64.1470823881682	female	16	35	white
117	5000	61.3266997484025	female	13	31	white
118	30000	74.3663964397274	male	12	38	white
119	70000	70.2101620207541	male	14	35	white
120	50000	71.106188031612	male	16	41	white
121	44000	62.594844043022	female	12	39	white
122	30000	64.0549647742882	female	14	43	white
123	10000	61.573618854396	female	16	40	white
124	23000	70.4801993905567	female	17	42	white
125	45000	71.1859069743659	male	17	62	white
126	15000	71.4336384225171	male	14	31	white
127	4000	70.2288485858589	female	14	71	white
128	17000	67.2808580445126	male	14	31	white
129	30000	63.7586912042461	female	12	32	white
130	27500	67.0865156073123	female	12	30	white
131	5688	61.679597878363	female	8	69	white
132	18000	62.285998323001	female	13	56	hispanic
133	43000	68.2924768726807	male	13	44	black
134	32000	61.5894825500436	female	14	44	black
135	10000	68.4177351850085	female	18	56	black
136	60000	73.9912551299203	male	13	45	white
137	21000	67.5610723162536	female	12	50	other
138	2400	62.3379296525382	female	16	22	white
139	1000	66.2400088959839	female	15	28	white
140	27000	68.0984727463219	male	12	27	white
141	6600	59.7708697339986	female	14	28	hispanic
142	16000	68.0633805643301	male	8	43	white
143	90000	71.6801480520517	male	12	26	white
144	8000	66.3597083494533	female	12	42	white
145	20000	68.3562582309823	male	10	32	white
146	15000	68.4565424812026	female	12	18	white
147	12000	68.7861042914446	female	12	60	white
148	24000	64.1022426583804	female	16	46	white
149	20000	65.1134854783304	female	14	39	white
150	19000	60.6491858377121	female	12	46	white
151	10000	72.1257029925473	male	12	49	white
152	40000	65.5107300695963	female	16	34	white
153	25000	67.931898314273	male	14	64	white
154	25000	70.4449232395273	male	12	24	white
155	25000	71.3658544581849	male	14	32	white
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160	24000	68.0777218828443	male	12	56	white
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162	13000	69.7157963842619	male	12	74	white
163	65000	68.2206725352444	male	16	46	white
164	7000	60.8838594953995	female	12	63	white
165	40000	68.4075396999251	male	18	63	white
166	15000	66.0019799831789	female	17	43	white
167	20000	69.7978899071459	male	16	25	white
168	20000	71.0107113404665	male	12	50	white
169	20000	65.1424107500352	female	12	42	white
170	25000	65.9671088184696	female	12	49	white
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172	25000	61.8766771967057	female	12	65	white
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1103	35000	67.8921973421238	male	16	30	hispanic
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1190	15000	61.1357995311264	female	18	82	white
1191	8000	63.6641635315027	female	12	33	white
1192	60000	71.9258358024526	male	12	50	white
1193	6000	68.3684862144291	male	12	27	white