Census Income Data Set

Predict whether income exceeds $50K/yr based on census data.

@kaggle.vivamoto_us_adult_income_update

Table List

3 tables(1.03 MB)

Census

Test

Train

Train

@kaggle.vivamoto_us_adult_income_update.train

355.28 KB
32561 rows
15 columns

age Age	workclass Workclass	fnlwgt Fnlwgt	education Education	education_num Education-num	marital_status Marital-status	occupation Occupation	relationship Relationship	race Race	sex Sex	capital_gain Capital-gain	hours_per_week Hours-per-week	native_country Native-country	income Income
39	State-gov	77516	Bachelors	13	Never-married	Adm-clerical	Not-in-family	White	Male	2174	40	United-States	<=50K
50	Self-emp-not-inc	83311	Bachelors	13	Married-civ-spouse	Exec-managerial	Husband	White	Male		13	United-States	<=50K
38	Private	215646	HS-grad	9	Divorced	Handlers-cleaners	Not-in-family	White	Male		40	United-States	<=50K
53	Private	234721	11th	7	Married-civ-spouse	Handlers-cleaners	Husband	Black	Male		40	United-States	<=50K
28	Private	338409	Bachelors	13	Married-civ-spouse	Prof-specialty	Wife	Black	Female		40	Cuba	<=50K
37	Private	284582	Masters	14	Married-civ-spouse	Exec-managerial	Wife	White	Female		40	United-States	<=50K
49	Private	160187	9th	5	Married-spouse-absent	Other-service	Not-in-family	Black	Female		16	Jamaica	<=50K
52	Self-emp-not-inc	209642	HS-grad	9	Married-civ-spouse	Exec-managerial	Husband	White	Male		45	United-States	>50K
31	Private	45781	Masters	14	Never-married	Prof-specialty	Not-in-family	White	Female	14084	50	United-States	>50K
42	Private	159449	Bachelors	13	Married-civ-spouse	Exec-managerial	Husband	White	Male	5178	40	United-States	>50K


CREATE TABLE train (
  "age" BIGINT,
  "workclass" VARCHAR,
  "fnlwgt" BIGINT,
  "education" VARCHAR,
  "education_num" BIGINT,
  "marital_status" VARCHAR,
  "occupation" VARCHAR,
  "relationship" VARCHAR,
  "race" VARCHAR,
  "sex" VARCHAR,
  "capital_gain" BIGINT,
  "capital_loss" BIGINT,
  "hours_per_week" BIGINT,
  "native_country" VARCHAR,
  "income" VARCHAR
);