Baselight

Finding Donors For CharityML

Nancy work for Udacity ML Charity Competition

@kaggle.nancyalaswad90_finding_donors_for_charityml

Census
@kaggle.nancyalaswad90_finding_donors_for_charityml.census

  • 257.97 KB
  • 45222 rows
  • 14 columns
age

Age

workclass

Workclass

education_level

Education Level

education_num

Education-num

marital_status

Marital-status

occupation

Occupation

relationship

Relationship

race

Race

sex

Sex

capital_gain

Capital-gain

capital_loss

Capital-loss

hours_per_week

Hours-per-week

native_country

Native-country

income

Income

39 State-gov Bachelors13 Never-married Adm-clerical Not-in-family White Male217440 United-States<=50K
50 Self-emp-not-inc Bachelors13 Married-civ-spouse Exec-managerial Husband White Male13 United-States<=50K
38 Private HS-grad9 Divorced Handlers-cleaners Not-in-family White Male40 United-States<=50K
53 Private 11th7 Married-civ-spouse Handlers-cleaners Husband Black Male40 United-States<=50K
28 Private Bachelors13 Married-civ-spouse Prof-specialty Wife Black Female40 Cuba<=50K
37 Private Masters14 Married-civ-spouse Exec-managerial Wife White Female40 United-States<=50K
49 Private 9th5 Married-spouse-absent Other-service Not-in-family Black Female16 Jamaica<=50K
52 Self-emp-not-inc HS-grad9 Married-civ-spouse Exec-managerial Husband White Male45 United-States>50K
31 Private Masters14 Never-married Prof-specialty Not-in-family White Female1408450 United-States>50K
42 Private Bachelors13 Married-civ-spouse Exec-managerial Husband White Male517840 United-States>50K

CREATE TABLE census (
  "age" BIGINT,
  "workclass" VARCHAR,
  "education_level" VARCHAR,
  "education_num" DOUBLE,
  "marital_status" VARCHAR,
  "occupation" VARCHAR,
  "relationship" VARCHAR,
  "race" VARCHAR,
  "sex" VARCHAR,
  "capital_gain" DOUBLE,
  "capital_loss" DOUBLE,
  "hours_per_week" DOUBLE,
  "native_country" VARCHAR,
  "income" VARCHAR
);

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