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 Series Title: Percent Distribution: Employed in Natural Resources, Construction, and Maintenance Occupations, Asian Women: NSA
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 2012 04 270·5
 2012 03 850·5
 2012 02 710.3
 2012 01 00.3
 2011 12  140·1
 2011 11  510.4
 2011 10  570.5
 2011 09  50.8
 2011 08  481·1
 2011 07  980·9
 2011 06  260.6
 2011 05  890.8
 2011 04  790·5
 2011 03  50.5
 2011 02  900·6
 2011 01  970·5
 2010 12 850·5
 2010 11 810·7
 2010 10 860·3
 2010 09 980·5
 2010 08 630·6
 2010 07 570.6
 2010 06 790.7
 2010 05 870.6
 2010 04 420.4
 2010 03 880·9
 2010 02 551·0
 2010 01 821.0
 2009 12  690·6
 2009 11  580·4
 2009 10  280·4
 2009 09  270.2
 2009 08  220.3
 2009 07  720·2
 2009 06  360.3
 2009 05  930·1
 2009 04  00·6
 2009 03  620.5
 2009 02  400.7
 2009 01  720·8
 2008 12 280.9
 2008 11 860.6
 2008 10 300·4
 2008 09 850.4
 2008 08 580.6
 2008 07 230·6
 2008 06 190.8
 2008 05 740·8
 2008 04 640·6
 2008 03 820.7
 2008 02 430.4
 2008 01 100·4
 2007 12  470·5
 2007 11  940·9
 2007 10  660.8
 2007 09  871.1
 2007 08  330·9
 2007 07  150·9
 2007 06  761.2
 2007 05  231.1
 2007 04  711.0
 2007 03  271·0
 2007 02  860.6
 2007 01  620.4
 2006 12 370·6
 2006 11 360.5
 2006 10 340.7
 2006 09 750·3
 2006 08 310.8
 2006 07 750·8
 2006 06 820·9
 2006 05 550·9
 2006 04 800·6
 2006 03 00.9
 2006 02 180.8
 2006 01 200.9
 2005 12  320·7
 2005 11  930·3
 2005 10  560.5
 2005 09  160·5
 2005 08  650·8
 2005 07  600·8
 2005 06  330·7
 2005 05  120·9
 2005 04  770·9
 2005 03  330.7
 2005 02  110·9
 2005 01  10.7
 2004 12 950·5
 2004 11 680·6
 2004 10 800.6
 2004 09 30.7
 2004 08 680·6
 2004 07 470.6
 2004 06 520·9
 2004 05 620.8
 2004 04 730·7
 2004 03 780.5
 2004 02 650·5
 2004 01 460·6
 2003 12  90.9
 2003 11  901.0
 2003 10  811·3
 2003 09  511·2
 2003 08  20·8
 2003 07  420·4
 2003 06  890·2
 2003 05  950.3
 2003 04  30·6
 2003 03  150.4
 2003 02  10·5
 2003 01  230.4
 2002 12 860·8
 2002 11 150·9
 2002 10 551.2
 2002 09 30.8
 2002 08 520.7
 2002 07 730·8
 2002 06 150·8
 2002 05 300.9
 2002 04 271·4
 2002 03 481.3
 2002 02 681.3
 2002 01 230.8
 2001 12  610·7
 2001 11  200.5
 2001 10  270.8
 2001 09  250.9
 2001 08  290.8
 2001 07  961·0
 2001 06  291.2
 2001 05  70·9
 2001 04  320·8
 2001 03  70·9
 2001 02  391.2
 2001 01  620.4
 2000 12 951.7
 2000 11 111.1
 2000 10 431·2
 2000 09 101.1
 2000 08 680.3
 2000 07 880·7
 2000 06 541·1
 2000 05 940·8
 2000 04 280·3
 2000 03 460·4
 2000 02 110.4
 2000 01 840.4
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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 Natural Resources, Construction, and Maintenance Occupations, Asian Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
   Transform this series  |  Display series in COPY/PASTE format  |  More series like this one

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