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2012 04 7664.8
2012 03 6965·5
2012 02 5865.2
2012 01 3364·9
2011 12 865.2
2011 11 164·8
2011 10 2865·4
2011 09 4065.5
2011 08 6465.2
2011 07 8764.1
2011 06 5664·4
2011 05 164.6
2011 04 9264.9
2011 03 1065·0
2011 02 5465·2
2011 01 6265.2
2010 12 6965.8
2010 11 7666.1
2010 10 6065.8
2010 09 9165·6
2010 08 9465·9
2010 07 1765.6
2010 06 3665.7
2010 05 8366·5
2010 04 9466.6
2010 03 8966·4
2010 02 7165·9
2010 01 5665.8
2009 12 1865·4
2009 11 7465·7
2009 10 7865·5
2009 09 5465·4
2009 08 4265.9
2009 07 7866.3
2009 06 9566.4
2009 05 4766.6
2009 04 6666.7
2009 03 3466.3
2009 02 8366.7
2009 01 2966.8
2008 12 1667·3
2008 11 9767·1
2008 10 3267·2
2008 09 1967·2
2008 08 4367·8
2008 07 5067.3
2008 06 5567·4
2008 05 6267.3
2008 04 2067.7
2008 03 9967.8
2008 02 8867·1
2008 01 2567·3
2007 12 5066·8
2007 11 7666.7
2007 10 9566.9
2007 09 567·2
2007 08 5767.3
2007 07 3767.6
2007 06 6466.9
2007 05 1867.0
2007 04 9167.1
2007 03 6467.3
2007 02 867.5
2007 01 1168·0
2006 12 2967·9
2006 11 6467·6
2006 10 6467·2
2006 09 5166·8
2006 08 7067·5
2006 07 6867.2
2006 06 9666·8
2006 05 3367·4
2006 04 4067·4
2006 03 3467.6
2006 02 9267.3
2006 01 7766.7
2005 12 8967·0
2005 11 4167·5
2005 10 6368.0
2005 09 2667·7
2005 08 9367·8
2005 07 9967.8
2005 06 4968.0
2005 05 4967.6
2005 04 5167·2
2005 03 3766.8
2005 02 1266·9
2005 01 4166·8
2004 12 9167.2
2004 11 1267·1
2004 10 4067·4
2004 09 2067.1
2004 08 6167·1
2004 07 767·3
2004 06 4666·6
2004 05 3266.6
2004 04 3767·1
2004 03 2767.6
2004 02 6867.1
2004 01 4467.5
2003 12 1966·7
2003 11 567.5
2003 10 6867·3
2003 09 5267.6
2003 08 3467.8
2003 07 9767.6
2003 06 3468·1
2003 05 7468.1
2003 04 3167·9
2003 03 8567·3
2003 02 8167·6
2003 01 5467·7
2002 12 8667·7
2002 11 7567·2
2002 10 4467.7
2002 09 6267.9
2002 08 9967·4
2002 07 9967.3
2002 06 8867·5
2002 05 9268.3
2002 04 9568.1
2002 03 1467.9
2002 02 9967·9
2002 01 6268·2
2001 12 2568·1
2001 11 167.5
2001 10 9267.7
2001 09 1868·3
2001 08 6568.3
2001 07 6768.3
2001 06 468·3
2001 05 2768·3
2001 04 1468·3
2001 03 4468·7
2001 02 9768.3
2001 01 8568.7
2000 12 9968.2
2000 11 8868.4
2000 10 6068·1
2000 09 1067·7
2000 08 6968.2
2000 07 8168·2
2000 06 668·5
2000 05 4768·8
2000 04 9968.9
2000 03 2967·4
2000 02 7267.9
2000 01 6568.2
1999 12 9268.7
1999 11 6469·1
1999 10 2169.1
1999 09 5769.4
1999 08 7068.8
1999 07 4369·2
1999 06 4268.8
1999 05 4368·8
1999 04 8668.8
1999 03 4868·3
1999 02 4768·4
1999 01 6868·9
1998 12 1468·3
1998 11 8468.6
1998 10 7368·8
1998 09 9967.9
1998 08 5568.2
1998 07 8568·6
1998 06 8568.3
1998 05 3267·5
1998 04 3468.2
1998 03 568·5
1998 02 6968·1
1998 01 8667.8
1997 12 267·9
1997 11 2867·5
1997 10 3967.6
1997 09 468·4
1997 08 3468·7
1997 07 5967·8
1997 06 3367.5
1997 05 5767·2
1997 04 3067·2
1997 03 3167.2
1997 02 1367.0
1997 01 3767.2
1996 12 1667.2
1996 11 9967·5
1996 10 6867·3
1996 09 6466.9
1996 08 4267.5
1996 07 4667·3
1996 06 966.6
1996 05 8266·7
1996 04 8466.3
1996 03 7866.4
1996 02 7666.2
1996 01 6166.7
1995 12 4266.3
1995 11 2766·8
1995 10 3166·3
1995 09 9465.7
1995 08 4165.7
1995 07 5065·6
1995 06 6266.1
1995 05 166·5
1995 04 3167.1
1995 03 2766·7
1995 02 8167.0
1995 01 2666.4
1994 12 8965·8
1994 11 6766·0
1994 10 2766·2
1994 09 3865·8
1994 08 1465·7
1994 07 9965·6
1994 06 6366·2
1994 05 3166·4
1994 04 3366·3
1994 03 8266·4
1994 02 7766·3
1994 01 2465.6
1993 12 9465.8
1993 11 9766.3
1993 10 8065·8
1993 09 6166·0
1993 08 7466·1
1993 07 4965.9
1993 06 1266.0
1993 05 1266·0
1993 04 7465.6
1993 03 7265.8
1993 02 3566·5
1993 01 7165·7
1992 12 1766.2
1992 11 2166.4
1992 10 3766.8
1992 09 5666·9
1992 08 5667·6
1992 07 7967.4
1992 06 3167.3
1992 05 1266·9
1992 04 6566·4
1992 03 5166·5
1992 02 5566·3
1992 01 966·3
1991 12 4466.2
1991 11 7065·6
1991 10 7166·2
1991 09 3966.9
1991 08 2066.1
1991 07 9266.2
1991 06 6966·4
1991 05 2366·3
1991 04 4266·9
1991 03 9966.8
1991 02 5966·5
1991 01 566.5
1990 12 8666·6
1990 11 9766.8
1990 10 8166·6
1990 09 5366·6
1990 08 5266·6
1990 07 1866.7
1990 06 9766.6
1990 05 6267·4
1990 04 6567·0
1990 03 2067.3
1990 02 9667.6
1990 01 5067·3
1989 12 7766.2
1989 11 8266.5
1989 10 8966.4
1989 09 6366·7
1989 08 6166.5
1989 07 1266.7
1989 06 1666·7
1989 05 6966·7
1989 04 2066.1
1989 03 4366.8
1989 02 3867.1
1989 01 6267.2
1988 12 7867·0
1988 11 2966.6
1988 10 4466.7
1988 09 6266·1
1988 08 8566.5
1988 07 5366·7
1988 06 4665.8
1988 05 1366.1
1988 04 1766·6
1988 03 2266.6
1988 02 8466·7
1988 01 8366.8
1987 12 7566·8
1987 11 6766.9
1987 10 1866.8
1987 09 6766.4
1987 08 8366.9
1987 07 4566·9
1987 06 3866.4
1987 05 8466·4
1987 04 9365·9
1987 03 3766·3
1987 02 5666·3
1987 01 7865·9
1986 12 7965·7
1986 11 5166.1
1986 10 1066·1
1986 09 1965·9
1986 08 4265·4
1986 07 1765·9
1986 06 6366.3
1986 05 066·4
1986 04 766.3
1986 03 9365·9
1986 02 265.5
1986 01 4165.6
1985 12 2465.9
1985 11 5965.7
1985 10 4265·4
1985 09 8565·7
1985 08 7065·3
1985 07 2465·2
1985 06 1965·7
1985 05 265.5
1985 04 4465·7
1985 03 1765·5
1985 02 9765·6
1985 01 8765·7
1984 12 7265.8
1984 11 9765.8
1984 10 6365·5
1984 09 5765.1
1984 08 565.7
1984 07 4465·3
1984 06 3065·0
1984 05 5865·2
1984 04 1764.5
1984 03 6664·9
1984 02 3765.0
1984 01 5864·4
1983 12 964·4
1983 11 9364·2
1983 10 4564·2
1983 09 5265.1
1983 08 664.9
1983 07 8365·2
1983 06 4465·1
1983 05 5864·9
1983 04 5964·9
1983 03 1865.1
1983 02 4665·2
1983 01 2265.5
1982 12 4365·1
1982 11 364.7
1982 10 8864.5
1982 09 1164·4
1982 08 5964·2
1982 07 7064·3
1982 06 3464.3
1982 05 2164·1
1982 04 3264.0
1982 03 7664.1
1982 02 7164·1
1982 01 7064.4
1981 12 1264.4
1981 11 464·5
1981 10 1364·5
1981 09 264.2
1981 08 7563·9
1981 07 5863·6
1981 06 9764·0
1981 05 8764.3
1981 04 2164.6
1981 03 7264.4
1981 02 8763.9
1981 01 1864·0
1980 12 7664.1
1980 11 164.4
1980 10 6964.4
1980 09 1664.0
1980 08 9064·6
1980 07 2864.5
1980 06 5763.8
1980 05 2364.3
1980 04 3764.2
1980 03 5863·7
1980 02 9064·2
1980 01 1064·5
1979 12 2064·4
1979 11 2464.4
1979 10 2965·0
1979 09 6964.7
1979 08 6364·6
1979 07 8364.9
1979 06 6364·6
1979 05 2264.2
1979 04 1664.2
1979 03 1564.9
1979 02 464·5
1979 01 1064·3
1978 12 5564.5
1978 11 2764·7
1978 10 9164·7
1978 09 564.9
1978 08 8064.3
1978 07 5264·3
1978 06 8664·8
1978 05 9964.8
1978 04 1764.6
1978 03 4664.6
1978 02 7764·5
1978 01 1264.5
1977 12 1664·4
1977 11 9063.5
1977 10 7763.0
1977 09 8963·1
1977 08 5263.3
1977 07 9162.6
1977 06 2563.3
1977 05 9763·4
1977 04 2663.2
1977 03 8163·4
1977 02 8263·5
1977 01 3362.8
1976 12 6463.0
1976 11 1663·1
1976 10 3762.2
1976 09 1362.3
1976 08 1562·8
1976 07 7862.6
1976 06 363·0
1976 05 8362·5
1976 04 5563.0
1976 03 7462.4
1976 02 1762·4
1976 01 1262.1
1975 12 8461·8
1975 11 3562·1
1975 10 4362·0
1975 09 9462.5
1975 08 2862.7
1975 07 1762·0
1975 06 6862·3
1975 05 4962.2
1975 04 3861.7
1975 03 462.3
1975 02 661·8
1975 01 1962·5
1974 12 8862·4
1974 11 062.7
1974 10 9363.2
1974 09 7563·2
1974 08 7862·9
1974 07 3962·8
1974 06 9462·8
1974 05 1063.2
1974 04 3663.1
1974 03 7662.5
1974 02 9563.6
1974 01 4464.0
1973 12 963·7
1973 11 9363.8
1973 10 1063·8
1973 09 2163·3
1973 08 7663.8
1973 07 9764·1
1973 06 7762.9
1973 05 963·0
1973 04 3463·5
1973 03 1963·9
1973 02 5963·6
1973 01 462.7
1972 12 1163.3
1972 11 1663.5
1972 10 4363·0
1972 09 2463.3
1972 08 5563.1
1972 07 7063·2
1972 06 4264·0
1972 05 1463·6
1972 04 4463·1
1972 03 8763·3
1972 02 9563.1
1972 01 4263·0
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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.
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Example 1: Get Unemployment Rates for people in Computer jobs |
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Example 2: Get Employment Data for Workers in the "Retail Trade" Industry |
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Example 3: Get Population Level Data for Workers |
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