Datasets:

mstz
/

adult

age int64	capital_gain float64	capital_loss float64	education int64	final_weight int64	hours_worked_per_week int64	marital_status string	native_country string	occupation string	race string	relationship string	is_male bool	workclass string	over_threshold int64
30	0	2,258	10	257,295	40	Never-married	South	Sales	Asian-Pac-Islander	Other-relative	true	Self-emp-not-inc	0
38	0	0	9	208,358	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Private	1
30	0	0	9	312,767	40	Never-married	United-States	Sales	Black	Unmarried	false	State-gov	0
38	0	0	6	200,904	40	Separated	United-States	Adm-clerical	Black	Unmarried	false	State-gov	0
45	10,520	0	13	154,430	50	Widowed	United-States	Prof-specialty	White	Not-in-family	false	Private	1
42	0	0	9	175,935	40	Married-civ-spouse	United-States	Machine-op-inspct	White	Husband	true	Private	0
34	0	0	9	112,584	40	Separated	United-States	?	White	Unmarried	false	?	0
18	0	0	7	205,218	20	Never-married	United-States	Sales	White	Own-child	false	Private	0
64	0	0	10	151,364	40	Never-married	United-States	Adm-clerical	White	Not-in-family	false	Private	0
18	0	0	9	210,574	20	Never-married	United-States	Sales	White	Own-child	false	Private	0
17	2,176	0	7	134,829	20	Never-married	United-States	Other-service	White	Own-child	true	Private	0
20	0	0	9	155,775	30	Never-married	United-States	Craft-repair	White	Own-child	true	Private	0
17	0	0	6	406,920	40	Never-married	United-States	?	White	Own-child	true	?	0
40	0	0	9	198,096	40	Married-civ-spouse	United-States	Machine-op-inspct	White	Husband	true	Private	1
75	25,124	0	16	152,519	20	Widowed	United-States	Prof-specialty	White	Not-in-family	true	Self-emp-inc	1
45	0	0	9	318,280	40	Widowed	United-States	Protective-serv	White	Not-in-family	true	Local-gov	1
52	0	0	12	174,421	32	Divorced	United-States	Prof-specialty	White	Unmarried	false	Private	0
55	15,024	0	13	73,684	65	Married-civ-spouse	United-States	Sales	White	Husband	true	Self-emp-not-inc	1
52	0	0	4	121,942	40	Married-civ-spouse	United-States	?	White	Husband	true	?	0
18	0	0	7	110,142	15	Never-married	United-States	Sales	White	Own-child	false	Private	0
24	0	0	10	267,181	35	Never-married	United-States	Other-service	White	Own-child	true	Private	0
22	0	0	9	113,464	40	Married-civ-spouse	Dominican-Republic	Transport-moving	Other	Husband	true	Private	0
33	0	0	9	133,278	40	Never-married	United-States	Adm-clerical	Black	Own-child	false	Private	0
37	0	0	13	108,320	45	Married-civ-spouse	United-States	Tech-support	White	Husband	true	Local-gov	1
32	0	0	11	33,117	40	Married-civ-spouse	United-States	Other-service	White	Husband	true	Private	0
33	0	2,444	11	194,901	42	Separated	United-States	Craft-repair	White	Not-in-family	true	Private	1
23	0	0	10	215,395	40	Never-married	United-States	Craft-repair	White	Not-in-family	true	Private	0
67	7,978	0	10	105,252	35	Divorced	United-States	Adm-clerical	White	Not-in-family	true	Private	0
24	0	0	9	126,822	45	Never-married	United-States	Adm-clerical	White	Unmarried	false	Private	0
47	0	0	10	134,671	40	Married-civ-spouse	United-States	Exec-managerial	White	Husband	true	Local-gov	0
20	0	0	9	406,641	30	Never-married	United-States	Adm-clerical	White	Not-in-family	false	Private	0
54	0	1,902	5	133,403	35	Married-civ-spouse	United-States	Machine-op-inspct	White	Husband	true	Private	0
39	0	0	10	50,096	80	Married-civ-spouse	United-States	Farming-fishing	White	Husband	true	Self-emp-not-inc	0
44	0	1,902	16	136,546	40	Married-civ-spouse	United-States	Prof-specialty	White	Husband	true	State-gov	1
25	0	0	13	193,701	38	Never-married	United-States	Other-service	White	Not-in-family	false	Private	0
27	0	0	10	89,598	60	Never-married	United-States	Adm-clerical	White	Unmarried	false	Private	0
23	0	0	9	154,641	40	Never-married	United-States	Handlers-cleaners	White	Own-child	true	Private	0
43	0	0	10	170,721	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Private	1
20	0	1,590	9	131,230	40	Never-married	United-States	Machine-op-inspct	White	Own-child	true	Private	0
40	0	0	14	255,824	40	Married-civ-spouse	United-States	Protective-serv	White	Husband	true	State-gov	1
50	7,688	0	10	196,307	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Local-gov	1
54	0	0	2	420,691	40	Married-civ-spouse	Mexico	Other-service	White	Husband	true	Private	0
46	0	0	11	328,669	42	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Private	0
41	0	0	13	180,138	50	Married-civ-spouse	Iran	Exec-managerial	White	Husband	true	Private	1
33	0	0	13	162,930	50	Married-civ-spouse	Italy	Prof-specialty	White	Husband	true	Private	0
25	0	0	13	220,931	43	Never-married	Peru	Prof-specialty	White	Not-in-family	true	Private	0
68	0	0	10	407,338	20	Married-civ-spouse	United-States	?	White	Husband	true	?	0
38	0	0	15	212,252	50	Married-civ-spouse	United-States	Prof-specialty	White	Wife	false	Private	1
31	0	0	13	42,900	37	Never-married	United-States	Tech-support	White	Not-in-family	true	Private	0
31	0	0	10	141,410	40	Never-married	United-States	Transport-moving	Black	Not-in-family	true	Private	0
45	0	0	13	77,927	40	Widowed	Philippines	Other-service	Asian-Pac-Islander	Own-child	false	Private	0
20	0	0	10	236,804	15	Never-married	United-States	Sales	White	Own-child	true	Private	0
45	0	0	13	34,419	30	Never-married	United-States	Transport-moving	White	Not-in-family	true	Private	0
44	0	1,741	12	139,161	40	Divorced	United-States	Adm-clerical	Black	Not-in-family	false	Federal-gov	0
39	0	0	13	99,452	50	Married-civ-spouse	United-States	Prof-specialty	White	Husband	true	Private	1
24	0	0	13	187,717	40	Never-married	United-States	Adm-clerical	White	Own-child	false	Private	0
51	0	0	10	190,333	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Federal-gov	0
31	0	0	9	118,551	40	Never-married	United-States	Tech-support	White	Not-in-family	false	Private	0
31	0	1,504	10	168,854	40	Never-married	United-States	Sales	White	Not-in-family	true	Private	0
30	0	0	7	426,017	19	Never-married	United-States	Other-service	White	Own-child	false	Private	0
52	0	2,559	15	198,863	60	Divorced	United-States	Exec-managerial	White	Not-in-family	true	Private	1
53	0	0	14	197,054	40	Married-civ-spouse	United-States	Prof-specialty	White	Husband	true	Local-gov	1
23	0	0	6	64,520	40	Never-married	United-States	Craft-repair	White	Not-in-family	true	Private	0
29	0	0	10	251,526	20	Married-civ-spouse	United-States	Tech-support	White	Wife	false	Private	0
59	0	0	9	188,047	40	Married-civ-spouse	United-States	Adm-clerical	Black	Husband	true	Federal-gov	0
20	0	0	10	38,455	10	Never-married	United-States	Craft-repair	White	Not-in-family	true	Local-gov	0
25	0	0	9	240,081	40	Never-married	United-States	Sales	Black	Own-child	true	Private	0
63	20,051	0	10	167,501	10	Married-civ-spouse	United-States	Prof-specialty	White	Wife	false	Self-emp-not-inc	1
33	0	0	9	102,270	30	Married-civ-spouse	United-States	Other-service	White	Wife	false	Private	0
33	0	0	12	342,458	56	Divorced	United-States	Protective-serv	White	Not-in-family	true	Local-gov	0
20	0	0	10	64,292	50	Never-married	United-States	Sales	White	Not-in-family	false	Private	0
50	0	0	14	251,240	40	Married-civ-spouse	United-States	Sales	White	Husband	true	Self-emp-inc	1
36	0	0	13	239,755	50	Married-civ-spouse	United-States	Exec-managerial	White	Husband	true	Private	1
55	0	0	7	169,611	40	Widowed	United-States	Adm-clerical	White	Unmarried	false	Private	0
33	0	0	13	217,304	40	Never-married	United-States	Adm-clerical	Black	Not-in-family	true	Local-gov	0
31	0	0	9	119,033	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Private	0
26	0	1,762	9	110,103	40	Never-married	United-States	Other-service	White	Not-in-family	false	Private	0
42	15,024	0	15	277,488	65	Married-civ-spouse	United-States	Prof-specialty	White	Husband	true	Self-emp-inc	1
40	0	0	11	327,573	40	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Private	0
48	0	0	13	67,725	45	Married-civ-spouse	United-States	Sales	White	Husband	true	Private	0
48	0	0	11	250,674	60	Married-civ-spouse	United-States	Craft-repair	White	Husband	true	Self-emp-inc	0
20	0	0	9	119,665	40	Never-married	United-States	Craft-repair	White	Own-child	true	Private	0
42	0	0	7	195,508	40	Married-civ-spouse	United-States	Transport-moving	Black	Husband	true	Private	0
31	0	0	9	233,371	45	Married-civ-spouse	United-States	?	Black	Wife	false	?	0
24	0	0	14	99,844	60	Never-married	United-States	Prof-specialty	White	Own-child	true	Private	0
26	0	1,848	9	366,219	60	Married-civ-spouse	United-States	Craft-repair	Black	Husband	true	Private	1
46	0	0	13	172,155	40	Married-civ-spouse	Peru	Machine-op-inspct	White	Husband	true	Private	0
37	0	0	9	312,766	40	Divorced	United-States	Other-service	White	Not-in-family	false	Private	0
49	0	0	10	36,032	40	Never-married	United-States	Exec-managerial	Black	Not-in-family	false	Private	0
25	0	0	13	177,812	40	Never-married	United-States	?	White	Not-in-family	true	?	0
20	0	0	10	73,266	40	Never-married	United-States	Transport-moving	Asian-Pac-Islander	Own-child	true	Private	0
43	0	0	9	169,076	40	Married-civ-spouse	United-States	Machine-op-inspct	Black	Husband	true	Private	0
25	0	0	9	192,449	40	Married-civ-spouse	United-States	Machine-op-inspct	White	Husband	true	Private	0
22	0	0	11	211,129	10	Never-married	?	Adm-clerical	White	Own-child	false	Local-gov	0
72	0	0	4	99,554	10	Married-civ-spouse	Poland	Handlers-cleaners	White	Wife	false	Private	0
27	5,013	0	9	181,667	46	Married-civ-spouse	Canada	Machine-op-inspct	White	Husband	true	Private	0
42	0	0	7	30,424	38	Separated	United-States	Other-service	White	Unmarried	false	Private	0
42	99,999	0	10	187,795	55	Married-civ-spouse	United-States	Exec-managerial	White	Husband	true	Private	1
18	0	0	9	187,790	40	Never-married	United-States	Adm-clerical	White	Own-child	false	Private	0
40	0	0	9	308,296	40	Divorced	United-States	Other-service	White	Own-child	false	Self-emp-not-inc	0

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Adult

The Adult dataset from the UCI ML repository. Census dataset including personal characteristic of a person, and their income threshold.

Configurations and tasks

Configuration	Task	Description
income	Binary classification	Classify the person's income as over or under the threshold.
income-no race	Binary classification	As `income`, but the `race` feature is removed.
race	Multiclass classification	Predict the race of the individual.

Usage

from datasets import load_dataset

dataset = load_dataset("mstz/adult", "income")["train"]

Features

Target feature changes according to the selected configuration and is always in last position in the dataset.

Feature	Type	Description
`age`	`[int64]`	Age of the person.
`capital_gain`	`[float64]`	Capital gained by the person.
`capital_loss`	`[float64]`	Capital lost by the person.
`education`	`[int8]`	Education level: the higher, the more educated the person.
`final_weight`	`[int64]`
`hours_worked_per_week`	`[int64]`	Hours worked per week.
`marital_status`	`[string]`	Marital status of the person.
`native_country`	`[string]`	Native country of the person.
`occupation`	`[string]`	Job of the person.
`race`	`[string]`	Race of the person.
`relationship`	`[string]`
`is_male`	`[bool]`	Man/Woman.
`workclass`	`[string]`	Type of job of the person.
over_threshold	`int8`	`1` for income `>= 50k$`, `0` otherwise.

Downloads last month: 190

Size of downloaded dataset files:

3.48 MB

Size of the auto-converted Parquet files:

600 kB

Number of rows:

36,633