Labor Python Library

From the CORGIS Dataset Project

By Austin Cory Bart acbart@vt.edu
Version 2.0.0, created 3/11/2016
Tags: labor, race, age, sex, gender, america, usa, census, employed, unemployed, employability, job, work, civilian, black, white, asian, government

Overview

The Current Population Survey (CPS) is a monthly survey of households conducted by the Bureau of Census for the Bureau of Labor Statistics. It provides a comprehensive body of data on the labor force, employment, unemployment, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics.

http://www.bls.gov/cps/home.htm

Explore Structure

Each row represents $MISSING_FIELD.

Index	Type	Example Value
0	dict	{ }
1	dict	(same structure)
2	dict	(same structure)
...	...	...

Key	Type	Example Value	Description
`"Time"`	dict	{ }
`"Data"`	dict	{ }

Key	Type	Example Value	Description
`"Month"`	int	`1`	$MISSING_FIELD
`"Month Name"`	str	`"January"`	$MISSING_FIELD
`"Year"`	int	`1972`	$MISSING_FIELD

Key	Type	Example Value
`"Civilian Noninstitutional Population"`	dict	{ }
`"Not In Labor Force"`	dict	{ }
`"Civilian Labor Force"`	dict	{ }
`"Employed"`	dict	{ }
`"Unemployed"`	dict	{ }

Key	Type	Example Value	Description
`"Asian"`	float	`0.0`	$MISSING_FIELD
`"Black or African American"`	float	`14332.0`	$MISSING_FIELD
`"White"`	float	`126749.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Asian"`	float	`0.0`	$MISSING_FIELD
`"Black or African American"`	float	`5998.0`	$MISSING_FIELD
`"White"`	float	`0.0`	$MISSING_FIELD

Key	Type	Example Value
`"Asian"`	dict	{ }
`"Black or African American"`	dict	{ }
`"White"`	dict	{ }

Key	Type	Example Value	Description
`"Counts"`	float	`0.0`	$MISSING_FIELD
`"Participation Rate"`	float	`0.0`	$MISSING_FIELD

Key	Type	Example Value
`"Asian"`	dict	{ }
`"Black or African American"`	dict	{ }
`"White"`	dict	{ }

Key	Type	Example Value	Description
`"Counts"`	float	`0.0`	$MISSING_FIELD
`"Unemployment Rate"`	float	`0.0`	$MISSING_FIELD

Key	Type	Example Value
`"Asian"`	dict	{ }
`"Black or African American"`	dict	{ }
`"White"`	dict	{ }

Key	Type	Example Value	Description
`"Counts"`	float	`0.0`	$MISSING_FIELD
`"Unemployment Rate"`	float	`0.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Participation Rate"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`8334.0`	$MISSING_FIELD
`"Men"`	float	`4180.0`	$MISSING_FIELD
`"Women"`	float	`3498.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`58.1`	$MISSING_FIELD
`"Men"`	float	`76.2`	$MISSING_FIELD
`"Women"`	float	`50.9`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Participation Rate"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`75608.0`	$MISSING_FIELD
`"Men"`	float	`43514.0`	$MISSING_FIELD
`"Women"`	float	`25728.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`59.7`	$MISSING_FIELD
`"Men"`	float	`81.7`	$MISSING_FIELD
`"Women"`	float	`42.7`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Employment-Population Ratio"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`7367.0`	$MISSING_FIELD
`"Men"`	float	`3802.0`	$MISSING_FIELD
`"Women"`	float	`3156.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`51.4`	$MISSING_FIELD
`"Men"`	float	`69.3`	$MISSING_FIELD
`"Women"`	float	`45.9`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Employment-Population Ratio"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`71169.0`	$MISSING_FIELD
`"Men"`	float	`41418.0`	$MISSING_FIELD
`"Women"`	float	`24403.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`56.1`	$MISSING_FIELD
`"Men"`	float	`77.7`	$MISSING_FIELD
`"Women"`	float	`40.5`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Unemployment Rate"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`967.0`	$MISSING_FIELD
`"Men"`	float	`378.0`	$MISSING_FIELD
`"Women"`	float	`343.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`11.6`	$MISSING_FIELD
`"Men"`	float	`9.0`	$MISSING_FIELD
`"Women"`	float	`9.8`	$MISSING_FIELD

Key	Type	Example Value	Description
`"Counts"`	dict	{ }
`"Unemployment Rate"`	dict	{ }

Key	Type	Example Value	Description
`"All"`	float	`4439.0`	$MISSING_FIELD
`"Men"`	float	`2096.0`	$MISSING_FIELD
`"Women"`	float	`1325.0`	$MISSING_FIELD

Key	Type	Example Value	Description
`"All"`	float	`5.9`	$MISSING_FIELD
`"Men"`	float	`4.8`	$MISSING_FIELD
`"Women"`	float	`5.1`	$MISSING_FIELD

Downloads

Download all of the following files.

Usage

import labor
result = labor.get_result()

Documentation

get_result(): Returns a list of dictionaries representing result.