Datasets:
File size: 3,641 Bytes
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---
dataset_info:
features:
- name: age
dtype: int64
- name: workclass
dtype: string
- name: fnlwgt
dtype: int64
- name: education
dtype: string
- name: education.num
dtype: int64
- name: marital.status
dtype: string
- name: occupation
dtype: string
- name: relationship
dtype: string
- name: race
dtype: string
- name: sex
dtype: string
- name: capital.gain
dtype: int64
- name: capital.loss
dtype: int64
- name: hours.per.week
dtype: int64
- name: native.country
dtype: string
- name: income
dtype: string
splits:
- name: train
num_bytes: 5316802
num_examples: 32561
download_size: 553790
dataset_size: 5316802
license: cc
language:
- en
pretty_name: adult-census-income
size_categories:
- 10K<n<100K
---
# adult-census-income
## Overview
The adult census income dataset is used for prediction tasks to determine whether a person makes over $50K a year.
It can also be used to explore biases in ML algorithms.
## Dataset Details
The original dataset, the [Adult Census Income](https://www.kaggle.com/datasets/uciml/adult-census-income), was created by Barry Becker from the 1994 Census database (USA),
to explore biases in ML algorithms. The prediction task of this dataset is to determine whether a person makes over 50K a year.
This data was extracted from the 1994 [Census Bureau database](https://www.census.gov/en.html) by Ronny Kohavi and Barry Becker (Data Mining and Visualization, Silicon Graphics). A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1) && (HRSWK>0)).
- Dataset Name: adult-census-income
- Language: English
- Total Size: 32,561 demonstrations
## Contents
The features and values that can be found in the adult census dataset are the following:
- **Income:** '>50K' (24,1%), '<=50K'(75,9%).
- **Age:** continuous.
- **Workclass:** Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.
- **fnlwgt:** continuous.
- **Education:** Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool.
- **Education.num:** continuous.
- **Marital.status:** Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse.
- **Occupation:** Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspect, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces.
- **Relationship:** Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried.
- **Race:** White, Asian-Pac-Islander, Amer-Indian--Eskimo, Other, Black.
- **Sex:** Female, Male.
- **Capital.gain:** continuous.
- **Capital.loss:** continuous.
- **Hours.per.week:** continuous.
- **Native.country:** United States, Cambodia, England, Puerto Rico, Canada, Germany, Outlying-US(Guam-USVI-etc), India, Japan, Greece, South, China, Cuba, Iran, Honduras,
Philippines, Italy, Poland, Jamaica, Vietnam, Mexico, Portugal, Ireland, France, Dominican Republic, Laos, Ecuador, Taiwan, Haiti, Columbia,
Hungary, Guatemala, Nicaragua, Scotland, Thailand, Yugoslavia, El-Salvador, Trinadad&Tobago, Peru, Hong, Holand-Netherlands.
## How to use
```python
from datasets import load_dataset
dataset = load_dataset("AiresPucrs/adult-census-income", split='train')
```
## License
This dataset is licensed under the [Creative Commons(CC)](https://creativecommons.org/publicdomain/zero/1.0/) License CC0 1.0.
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