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 Series Title: Percent Distribution: Employed in Construction and Extraction Occupations, Asian Women: NSA
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 2012 04 200·1
 2012 03 620·1
 2012 02 180.0
 2012 01 150·0
 2011 12  60.1
 2011 11  440·1
 2011 10  860·1
 2011 09  160.2
 2011 08  30.3
 2011 07  690.1
 2011 06  980·0
 2011 05  600·0
 2011 04  600.0
 2011 03  170·1
 2011 02  680.1
 2011 01  900·1
 2010 12 520.1
 2010 11 960·2
 2010 10 340.1
 2010 09 760·2
 2010 08 820·1
 2010 07 380·0
 2010 06 580.0
 2010 05 120·0
 2010 04 720.1
 2010 03 980.3
 2010 02 280.4
 2010 01 160·4
 2009 12  750.2
 2009 11  580.2
 2009 10  580.1
 2009 09  340.0
 2009 08  660.0
 2009 07  260.0
 2009 06  840.0
 2009 05  340.0
 2009 04  440·2
 2009 03  320·1
 2009 02  700.2
 2009 01  110.2
 2008 12 350·2
 2008 08 330·1
 2008 07 40·3
 2008 06 830·1
 2008 05 900.1
 2008 04 120·1
 2008 03 990·3
 2008 02 940.0
 2008 01 840·0
 2007 12  740.0
 2007 11  920.0
 2007 10  150·0
 2007 09  170.4
 2007 08  510.2
 2007 07  470.1
 2007 06  380·2
 2007 05  150·1
 2007 04  10·0
 2007 03  510·1
 2007 02  840.1
 2007 01  280.2
 2006 12 30.3
 2006 11 170.3
 2006 10 950.3
 2006 09 320.2
 2006 08 660·3
 2006 07 840·3
 2006 06 430·2
 2006 05 270·1
 2006 04 210.1
 2006 03 130.2
 2006 02 190.4
 2006 01 380.3
 2005 12  250·2
 2005 11  930·1
 2005 10  450·1
 2005 09  160·1
 2005 08  580·1
 2005 07  380.1
 2005 06  630·1
 2005 03  360.1
 2005 02  280·1
 2005 01  830·2
 2004 10 430.1
 2004 07 980.1
 2004 06 670·1
 2004 05 940.2
 2004 04 790.1
 2004 03 290.0
 2004 02 300·0
 2004 01 570.0
 2003 12  910.0
 2003 11  770·0
 2003 10  10.2
 2003 09  850·3
 2003 08  210·2
 2003 07  200.2
 2003 06  840·0
 2003 05  160·0
 2003 04  410.0
 2003 03  560.0
 2003 01  130·1
 2002 12 140.2
 2002 11 430.2
 2002 10 120·3
 2002 09 430.1
 2002 07 660.0
 2002 06 460·0
 2002 05 380·0
 2002 04 560·1
 2002 03 840·1
 2002 02 960·0
 2002 01 90·0
 2001 11  590·0
 2001 10  80·0
 2001 09  610.1
 2001 08  250·0
 2001 07  840.1
 2001 06  990·2
 2001 05  350·1
 2001 04  130.1
 2001 03  870·1
 2001 02  460·1
 2001 01  370.0
 2000 12 220.6
 2000 11 500.5
 2000 10 610·7
 2000 09 120.4
 2000 07 280·1
 2000 06 790.2
 2000 05 820.1
 2000 04 280·1
 2000 03 310.1
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: Alternative Measures of Labor Underutilization
Unemployment Rate: Gender
Unemployment Rate: Black: Gender
Unemployment Rate: White: Gender
Unemployment Rate: Race
Unemployment Rate: Age: 16/25/35/45/55
Unemployment Rate: Education
Unemployment Rate: Nonagricultural Industry
Unemployment Rate: Job Category
Median Weeks Unemployed: Age
Median Weeks Unemployed: Race


The US Labor Force Dataset from the BLS contains nearly 15,000 series.
These series are subcategories of the popular series of:

Civilian Labor Force (subcategories)
Employment Level (subcategories)
Unemployment Level (subcategories)
US Unemployment Rate (subcategories)
Population (subcategories)
Employment-Population Ratio (subcategories)
Median Weeks Unemployed (subcategories)
Percent Distribution (subcategories)
Average Hours At Work (subcategories)
Of Total Unemployed (subcategories)

These basic measures are augmented by:

Population
Labor Force Participation Rate
Employment-Population Ratio
Not in Labor Force
Number at work
Average hours at work
Multiple jobholders
Average number of search methods used
Number At work part-time

These series can be subdivided by:

Sex:

Male
Female

Race and Ethnicity:

White
Black
Hispanic
Mexican
Puerto Rican
Cuban

Age:

16 years and over (default)
14_yrs._&_over
16-17_yrs.
16-19_yrs.
16-21_yrs.
16-24_yrs.
18-19_yrs.
20_yrs._&_over
20-24_yrs.
20-64_yrs.
25_yrs._&_over
25-29_yrs.
25-34_yrs.
25-54_yrs.
25-59_yrs.
30-34_yrs.
35-39_yrs.
35-44_yrs.
40-44_yrs.
45_yrs._&_over
45-49_yrs.
45-54_yrs.
50-54_yrs.
55_yrs._&_over
55-59_yrs.
55-64_yrs.
60-61_yrs.
60-64_yrs.
62-64_yrs.
65_yrs._&_over
65-69_yrs.
70_yrs._&_over

Class Of Worker:

Wage_And_Salary_Workers
Private_Wage_And_Salary_Workers
Government_Wage_And_Salary_Workers
Self-employed_Workers
Unpaid_Family_Workers

Industry:

Agriculture_Service
Furniture_And_Fixtures
Motor_Vehicles_&_Motor_Vehicle_Equipment
Aircraft
Tobacco
Eating_And_Drinking
Private_Households
Hospital
Postal
Federal
State
Local
Goods_Producing
Service_Producing
Agriculture_(Excludes_Forestry_And_Fisheries)
Forestry_And_Fisheries
Nonagricultural
Mining
Construction
Manufacturing
Manufacturing,_Durables
Lumber_And_Wood_Products,_Except_Furniture
Stone,_Clay,_And_Glass_Products
Primary_Metal
Fabricated_Metal
Machinery
Electrical_machinery,_equipment,_&_supplies
Transportation_Equipment
Professional_&_photographic_equipment_&_watches
Other_transportation_equipment
Fabricated_Metals
Manufacturing,_Nondurables
Food_And_Kindred_Products
Textile_Mill_Products
Apparel_And_Other_Fabricated_Textile_Products
Paper_And_Allied_Products
Printing,_Publishing,_And_Allied_Industries
Chemicals_And_Allied_Products
Petroleum_And_Coal_Products
Rubber_And_Miscellaneous_Plastic_Products
Leather_And_Leather_Products
Transportation,_Communication,_And_Other_Public_Utilities
Transportation
Transportation_Other_Than_Railroad_And_Railway_Express
Communications_And_Other_Public_Utilities
Communications
Trade
Wholesale_Trade
Retail_Trade
Service_Industries
Finance,_Insurance,_And_Real_Estate
Insurance_And_Real_Estate
Banking_And_Other_Financial_Organizations
Business_And_Repair_Services
Businesses
Repair_Services
Personal_Services
Entertainment_And_Recreation_Services
Professional_And_Related_Services
Medical
Educational_Services
Welfare_And_Religious_Services
Public_Administration

Occupation:

Managerial_&_professional_specialty_occupation
Executive,_administration,_&_managerial
Officials_&_administration,_public_administation
Management_Related_Occupations
Professional_Specialty_Occupations
Engineers
Math_&_Computer_Scientists
Natural_scientists
Health_Diagnosing_Occupations
Health_Assessment_&_Treating
Teachers,_college_&_university
Lawyers_&_Judges
Technical,_sales,_administration_support
Technicians_&_related_support_occupations
Health_technologists_&_technicians
Engineering_&_science_technicians
Technicians
Sales_Occupations
Supervisors_&_Proprietors
Sales_reps,_finance_&_business_services
Sales_reps,_commodities
Sales,_retail_&_personal
Sales_Related_Occupations
Administrative_support
Supervisors
Computer_Equipment_Operators
Secretaries,_stenographers,_&_typists
Financial_Records_Processing
Mail_&_Message_Distributing
Service_Occupation
Private_Household
Protective_Services
Food_Service
Health_Service
Cleaning_&_Building_Service
Personal_Service
Precision_Production,_Craft,_Repair
Mechanics_&_Repairers
Construction_Trades
Operators,_Fabricators,_Laborers
Machine_operators,_assemblers,_inspectors
Operators_&_tenders
Fabricators,_assemblers,_inspectors,_samplers
Transportation,_material_moving
Motor_vehicle_operators
Handlers,_equipment_cleaners,_helpers,_laborers
Construction_Laborers
Freight,_stock_material_handlers
Farming,_Forestry,_Fishing
Farm_Operators_&_Managers
Farm_workers_&_related_occupations
Forestry_&_fishing_occupations

Input your search text below.
or alter the examples after this blank template.







      Example 1: Get Unemployment Rates for people in Computer jobs







      Example 2: Get Employment Data for Workers in the "Retail Trade" Industry







      Example 3: Get Population Level Data for Workers





 Series Title: Percent Distribution: Employed in Construction and Extraction Occupations, Asian Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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