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2012 04 1467.3
2012 03 4468·4
2012 02 2368.1
2012 01 9168.4
2011 12 1369·0
2011 11 5568·5
2011 10 8568·5
2011 09 268.3
2011 08 8568·7
2011 07 7167·9
2011 06 5468·3
2011 05 1867·8
2011 04 8068.5
2011 03 7268.6
2011 02 4468.2
2011 01 8368.3
2010 12 7368·9
2010 11 6769·1
2010 10 9169·0
2010 09 6669·1
2010 08 6569.4
2010 07 8769·1
2010 06 5969.4
2010 05 6170.4
2010 04 8169.9
2010 03 8870.4
2010 02 3569.3
2010 01 8869.3
2009 12 7168·8
2009 11 5169·1
2009 10 3469·1
2009 09 9068.5
2009 08 1269·4
2009 07 8569·5
2009 06 9169.5
2009 05 3770.2
2009 04 370.2
2009 03 1969·9
2009 02 7170.4
2009 01 2370·5
2008 12 6970.8
2008 11 1270·4
2008 10 6270.9
2008 09 6771.4
2008 08 6271.8
2008 07 4371.3
2008 06 7671.5
2008 05 1370·9
2008 04 5671.2
2008 03 2171·3
2008 02 5071·4
2008 01 3171.2
2007 12 5270·6
2007 11 7770.9
2007 10 4970.6
2007 09 1471·2
2007 08 7571·7
2007 07 6771·9
2007 06 5970·4
2007 05 8270.7
2007 04 7671·2
2007 03 7371·2
2007 02 9571.4
2007 01 7872·0
2006 12 3071·6
2006 11 271·2
2006 10 9271·0
2006 09 7270.9
2006 08 3770.7
2006 07 8570·9
2006 06 1670.4
2006 05 5971·7
2006 04 2471.6
2006 03 7971·6
2006 02 5371·3
2006 01 5669.9
2005 12 3970·3
2005 11 6670·7
2005 10 1671·6
2005 09 971·8
2005 08 5972·2
2005 07 5272.5
2005 06 4372.3
2005 05 8671·7
2005 04 8571.1
2005 03 6970.4
2005 02 9770.5
2005 01 8270.1
2004 12 4071.0
2004 11 7471·2
2004 10 6771.0
2004 09 1570·9
2004 08 7670·6
2004 07 4770·3
2004 06 6470.6
2004 05 3070·4
2004 04 6970·2
2004 03 9771·2
2004 02 2770·8
2004 01 9772·1
2003 12 1871·4
2003 11 5371.4
2003 10 1871.0
2003 09 871.7
2003 08 4971·2
2003 07 7471·4
2003 06 2772.0
2003 05 8471·8
2003 04 1371.7
2003 03 4170·9
2003 02 6472·0
2003 01 6871·3
2002 12 8470.9
2002 11 6070·2
2002 10 6972·0
2002 09 3072·4
2002 08 6371·7
2002 07 6371.6
2002 06 472·0
2002 05 6473.0
2002 04 7672.8
2002 03 773·0
2002 02 5772·3
2002 01 8872·6
2001 12 7372.5
2001 11 7371·2
2001 10 4171.1
2001 09 4772·4
2001 08 2972·3
2001 07 6872.1
2001 06 9471.5
2001 05 1171·8
2001 04 4472.3
2001 03 2372.4
2001 02 7972.4
2001 01 7372·7
2000 12 4572·6
2000 11 9672.6
2000 10 8472.6
2000 09 5272·0
2000 08 8172.4
2000 07 6872.3
2000 06 2172·3
2000 05 9272.5
2000 04 2973.2
2000 03 4569.2
2000 02 2870.0
2000 01 6470.4
1999 12 8772·4
1999 11 5972.7
1999 10 6973.0
1999 09 6072·7
1999 08 8272·2
1999 07 6771·9
1999 06 3172.4
1999 05 072.8
1999 04 6471.9
1999 03 5171.6
1999 02 2772.0
1999 01 2972.8
1998 12 971·9
1998 11 1672.3
1998 10 9573·2
1998 09 1472·1
1998 08 1672·5
1998 07 9573·1
1998 06 9873·1
1998 05 5172.1
1998 04 1273·0
1998 03 4572·8
1998 02 2471.8
1998 01 5972.2
1997 12 4672·0
1997 11 4672.0
1997 10 8572.3
1997 09 8173·0
1997 08 9473.8
1997 07 772·4
1997 06 2172.6
1997 05 8771·6
1997 04 5771·5
1997 03 5771.7
1997 02 9271·3
1997 01 7171.7
1996 12 5971·8
1996 11 5472.7
1996 10 8872.3
1996 09 5272.5
1996 08 5273·2
1996 07 8072·5
1996 06 2171.9
1996 05 7572.3
1996 04 1071·7
1996 03 4172·3
1996 02 2972.2
1996 01 772.1
1995 12 3471·6
1995 11 6971.6
1995 10 7571·7
1995 09 4472.1
1995 08 4971.9
1995 07 2171.7
1995 06 4872.6
1995 05 573.0
1995 04 773.6
1995 03 7773·6
1995 02 5873.6
1995 01 3473·3
1994 12 8172·8
1994 11 4572.6
1994 10 4672.7
1994 09 071.9
1994 08 7371·6
1994 07 5771.9
1994 06 7372·1
1994 05 9673.3
1994 04 772.6
1994 03 6972.3
1994 02 2873·0
1994 01 4372·1
1993 12 3571.8
1993 11 6273.1
1993 10 2372.5
1993 09 8573.2
1993 08 3273·8
1993 07 4473.5
1993 06 9673.3
1993 05 9073.3
1993 04 9772·6
1993 03 4573.5
1993 02 1174.1
1993 01 5273·6
1992 12 5873·1
1992 11 2373·9
1992 10 5474.1
1992 09 9174·3
1992 08 6374.8
1992 07 6074·6
1992 06 4074·8
1992 05 5274·7
1992 04 8874·2
1992 03 6174.5
1992 02 574.2
1992 01 274·4
1991 12 3474.3
1991 11 5973·7
1991 10 1374.1
1991 09 3674·6
1991 08 2673.9
1991 07 1074·6
1991 06 5174.5
1991 05 7473·9
1991 04 1475.4
1991 03 9575.6
1991 02 3375.3
1991 01 6074.8
1990 12 7475·1
1990 11 2375·3
1990 10 9775.1
1990 09 6175·1
1990 08 775·0
1990 07 2375·1
1990 06 474.8
1990 05 7474.9
1990 04 3674·8
1990 03 5374.8
1990 02 4475·0
1990 01 1774·9
1989 12 1473·9
1989 11 9474.0
1989 10 2974·1
1989 09 3474·5
1989 08 1674.1
1989 07 5474.1
1989 06 9774·1
1989 05 9374.4
1989 04 4174·0
1989 03 6374.7
1989 02 1174.7
1989 01 9175.0
1988 12 1574·5
1988 11 7874.2
1988 10 5874.5
1988 09 4474.1
1988 08 8974·7
1988 07 8173.9
1988 06 5274.2
1988 05 9974.6
1988 04 3775·2
1988 03 7974.8
1988 02 3075·3
1988 01 2374.7
1987 12 6174·4
1987 11 374.6
1987 10 5674·4
1987 09 1174.6
1987 08 8675·0
1987 07 975·3
1987 06 1774.7
1987 05 8275.0
1987 04 6274·4
1987 03 8174.6
1987 02 2774.6
1987 01 8074.5
1986 12 6474·7
1986 11 2374·9
1986 10 2275·0
1986 09 7474·6
1986 08 9373.9
1986 07 6875.0
1986 06 6675·5
1986 05 5975·2
1986 04 7575·0
1986 03 7375·0
1986 02 4874.4
1986 01 5474·9
1985 12 5974.6
1985 11 1874.5
1985 10 7974.6
1985 09 274.9
1985 08 2174·1
1985 07 1274.0
1985 06 9774.1
1985 05 7374.2
1985 04 6274.1
1985 03 8474.1
1985 02 6674·8
1985 01 6274·4
1984 12 675·0
1984 11 9374·8
1984 10 7475.1
1984 09 8674·6
1984 08 574·9
1984 07 1974·9
1984 06 3274·5
1984 05 9174.7
1984 04 3374·0
1984 03 7075·0
1984 02 8075·6
1984 01 4574·9
1983 12 9274.7
1983 11 7674·8
1983 10 8174·3
1983 09 4375.2
1983 08 575.4
1983 07 9575.8
1983 06 2175·7
1983 05 375.0
1983 04 2575.2
1983 03 874·8
1983 02 1375·0
1983 01 7075·6
1982 12 2675·6
1982 11 2275·5
1982 10 9774.9
1982 09 1474·8
1982 08 874·2
1982 07 6874·5
1982 06 3474.4
1982 05 2774·5
1982 04 9774·5
1982 03 374·5
1982 02 1374·7
1982 01 3074.6
1981 12 4474.6
1981 11 1074·3
1981 10 4675.0
1981 09 6674·8
1981 08 2374·4
1981 07 9373.8
1981 06 7274·1
1981 05 575.5
1981 04 3674·6
1981 03 8674·9
1981 02 5374.3
1981 01 4074.3
1980 12 774·3
1980 11 4474·8
1980 10 7775.0
1980 09 9275.3
1980 08 8775·7
1980 07 4975.6
1980 06 5774·9
1980 05 374·9
1980 04 5175·3
1980 03 974.8
1980 02 3075.5
1980 01 4375.9
1979 12 075·9
1979 11 5475.8
1979 10 6176.7
1979 09 776·9
1979 08 5976·5
1979 07 4176·8
1979 06 3676.4
1979 05 1375·9
1979 04 7975·7
1979 03 5276.2
1979 02 6976.1
1979 01 676.0
1978 12 3476.4
1978 11 9476·6
1978 10 9776.1
1978 09 5476·2
1978 08 2675·1
1978 07 9775·8
1978 06 8376·2
1978 05 5276.4
1978 04 7976.5
1978 03 2076·4
1978 02 1676.1
1978 01 2076.6
1977 12 4475.8
1977 11 4375·4
1977 10 875·0
1977 09 074·4
1977 08 9775·7
1977 07 7375·1
1977 06 9776·0
1977 05 6275·5
1977 04 3875·7
1977 03 4176.4
1977 02 4576·5
1977 01 176·1
1976 12 9175.9
1976 11 576·0
1976 10 4275.1
1976 09 3675.3
1976 08 975.7
1976 07 4675.4
1976 06 9975·9
1976 05 1075.3
1976 04 6575·5
1976 03 7174.2
1976 02 5574·8
1976 01 9374·8
1975 12 6175.2
1975 11 1175.8
1975 10 7275.8
1975 09 7977.0
1975 08 2277·2
1975 07 2376·3
1975 06 3975·8
1975 05 8775·9
1975 04 9775.3
1975 03 8875·8
1975 02 6775.7
1975 01 6176·9
1974 12 6476·7
1974 11 1377.2
1974 10 9677.4
1974 09 7177.0
1974 08 2177·0
1974 07 3176·6
1974 06 8877.6
1974 05 1077.8
1974 04 9478·0
1974 03 9778·5
1974 02 3179.0
1974 01 9879·4
1973 12 3578·5
1973 11 9378·5
1973 10 3878.7
1973 09 7977·7
1973 08 1778·3
1973 07 2578·7
1973 06 4678·3
1973 05 2178.1
1973 04 4278·6
1973 03 2679·1
1973 02 1978.4
1973 01 2077.4
1972 12 3578.0
1972 11 5278·1
1972 10 4478.1
1972 09 9478.6
1972 08 4678·7
1972 07 8578·8
1972 06 3579.4
1972 05 8778.7
1972 04 5178.6
1972 03 3178.7
1972 02 2978·3
1972 01 6977·6
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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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