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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 16-17 years, Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 240.
 2012 03 100·
 2012 02 960.
 2012 01 160.
 2011 12  28
 2011 11  931·
 2011 10  722·
 2011 09  581·
 2011 08  23
 2011 07  99
 2011 06  740·
 2011 05  232.
 2011 04  600·
 2011 03  100·
 2011 02  142·
 2011 01  570.
 2010 12 140·
 2010 11 33
 2010 10 322·
 2010 09 270.
 2010 08 853.
 2010 07 993.
 2010 06 8915·
 2010 05 28
 2010 04 03.
 2010 03 654.
 2010 02 731·
 2010 01 801·
 2009 12  72·
 2009 11  130.
 2009 10  980·
 2009 09  260.
 2009 08  841.
 2009 07  501·
 2009 06  14·
 2009 02  365.
 2009 01  293·
 2008 12 63·
 2008 11 452.
 2008 08 32·
 2008 07 692.
 2008 06 398.
 2008 05 184.
 2008 04 473·
 2008 03 546·
 2008 02 302·
 2008 01 336.
 2007 12  126·
 2007 11  593·
 2007 10  866.
 2007 09  283·
 2007 08  672·
 2007 07  843.
 2007 06  381·
 2007 04  660·
 2007 03  62·
 2007 02  56
 2007 01  443.
 2006 12 344.
 2006 11 484·
 2006 10 241.
 2006 08 843·
 2006 07 455.
 2006 06 385.
 2006 05 643.
 2006 04 660·
 2006 03 391·
 2005 11  45
 2005 10  763·
 2005 09  214.
 2005 08  763.
 2005 07  623.
 2005 06  851.
 2005 05  65.
 2005 04  452·
 2005 03  103·
 2005 02  432·
 2004 09 23·
 2004 08 60
 2004 07 3110·
 2004 06 2413.
 2004 05 166.
 2004 04 574.
 2004 03 963.
 2004 02 292.
 2004 01 803·
 2003 11  10·
 2003 10  983.
 2003 09  824·
 2003 08  5012.
 2003 07  7811.
 2003 06  5610.
 2003 05  364·
 2003 04  81·
 2003 03  11.
 2003 02  151.
 2003 01  643·
 2002 12 602.
 2002 11 104.
 2002 10 442·
 2002 07 682.
 2002 06 396·
 2002 05 652.
 2002 03 363.
 2002 02 723·
 2002 01 04.
 2001 12  565·
 2001 10  120.
 2001 08  281·
 2001 07  262·
 2001 06  950.
 2001 05  15
 2001 03  100.
 2001 02  23
 2001 01  202·
 2000 12 143·
 2000 10 19
 2000 09 234·
 2000 08 944.
 2000 07 46·
 2000 05 801.
 2000 04 822·
 2000 03 52·
 1999 12  35.
 1999 09  441.
 1999 08  826·
 1999 07  666.
 1999 06  564·
 1999 05  865.
 1998 11 301.
 1998 10 142·
 1998 09 324.
 1998 08 61·
 1998 07 583·
 1998 06 132.
 1998 05 252.
 1998 04 30
 1998 03 213·
 1998 02 500·
 1997 12  542.
 1997 11  93·
 1997 10  27.
 1997 09  387·
 1997 08  635.
 1997 07  177.
 1997 06  74.
 1997 05  16
 1997 04  226.
 1997 03  556·
 1997 01  685.
 1996 12 460.
 1996 11 25
 1996 10 480.
 1996 09 420.
 1996 08 151.
 1996 07 901·
 1996 06 470.
 1996 05 93·
 1996 04 38
 1996 03 625.
 1996 02 28
 1995 12  781.
 1995 11  512.
 1995 10  101.
 1995 09  90
 1995 08  791.
 1995 07  18
 1995 06  282·
 1995 05  592·
 1995 04  693.
 1995 03  273.
 1995 01  353·
 1994 11 850·
 1994 10 302·
 1994 09 906.
 1994 08 761.
 1994 07 443.
 1994 06 684·
 1994 04 450·
 1994 03 202·
 1994 02 360·
 1994 01 156.
 1993 12  562.
 1993 11  60
 1993 10  871.
 1993 09  283.
 1993 08  9
 1993 07  1612·
 1993 06  479.
 1993 05  881.
 1993 03  193.
 1993 02  321.
 1992 12 901.
 1992 11 23.
 1992 10 224.
 1992 09 773·
 1992 08 196.
 1992 07 26.
 1992 06 825.
 1992 05 454.
 1992 04 583·
 1992 03 442.
 1992 02 876·
 1992 01 565.
 1991 12  57
 1991 11  105·
 1991 10  508·
 1991 09  53
 1991 08  926.
 1991 07  611.
 1991 06  74.
 1991 05  76.
 1991 04  633·
 1991 03  643·
 1991 01  241.
 1990 12 91·
 1990 11 96
 1990 09 424.
 1990 08 863.
 1990 07 817·
 1990 05 411·
 1990 04 195·
 1990 03 75.
 1990 02 662.
 1990 01 742·
 1989 12  43.
 1989 11  264.
 1989 10  333.
 1989 09  942.
 1989 08  275.
 1989 07  45·
 1989 06  774.
 1989 05  28
 1989 04  463.
 1989 03  313·
 1989 01  16
 1988 12 253·
 1988 11 423.
 1988 10 173.
 1988 09 955.
 1988 08 617·
 1988 07 219.
 1988 06 310·
 1988 05 83
 1988 04 363.
 1988 03 152.
 1988 02 502.
 1988 01 732.
 1987 11  773.
 1987 08  826.
 1987 07  4613.
 1987 06  8610·
 1987 05  327·
 1987 04  24.
 1987 03  41·
 1987 02  658·
 1987 01  782·
 1986 11 821·
 1986 10 631·
 1986 09 804.
 1986 08 158·
 1986 07 54
 1986 06 8519.
 1986 05 236.
 1986 04 686.
 1986 03 755·
 1986 02 577.
 1986 01 164·
 1985 12  88
 1985 10  253.
 1985 09  942·
 1985 08  1
 1985 07  505.
 1985 06  136·
 1985 05  322.
 1985 04  498·
 1985 03  553·
 1985 02  681.
 1985 01  342.
 1984 12 524.
 1984 11 28
 1984 10 491.
 1984 09 894.
 1984 08 319·
 1984 07 1810.
 1984 06 378.
 1984 05 107.
 1984 04 294.
 1984 03 3
 1984 02 372·
 1984 01 332.
 1983 11  151·
 1983 10  824·
 1983 09  834·
 1983 08  236·
 1983 07  845·
 1983 06  807·
 1983 05  315.
 1983 04  674·
 1983 03  554·
 1983 02  473·
 1983 01  61
 1982 12 782·
 1982 11 722·
 1982 10 611·
 1982 09 814·
 1982 08 9313.
 1982 07 414.
 1982 06 1913.
 1982 05 231.
 1982 04 773.
 1982 03 45
 1982 02 49
 1982 01 443·
 1981 12  163·
 1981 11  14
 1981 10  010·
 1981 09  2318.
 1981 08  2312.
 1981 07  5613·
 1981 06  4915·
 1981 05  7010·
 1981 04  379.
 1981 03  406.
 1981 02  943.
 1981 01  145·
 1980 12 204.
 1980 11 595·
 1980 10 626.
 1980 09 137·
 1980 08 609·
 1980 07 3428·
 1980 06 228·
 1980 05 4919·
 1980 04 7017.
 1980 03 78·
 1980 02 922.
 1980 01 272.
 1979 12  893.
 1979 11  493.
 1979 10  305.
 1979 09  80
 1979 08  7815·
 1979 07  5214·
 1979 06  429.
 1979 05  656·
 1979 04  259.
 1979 03  3810·
 1979 02  789·
 1979 01  623.
 1978 12 456·
 1978 11 498·
 1978 10 156·
 1978 09 7910·
 1978 08 7425.
 1978 07 5430·
 1978 06 5219.
 1978 05 4714.
 1978 04 754.
 1978 03 49
 1978 02 1411·
 1978 01 2311.
 1977 12  369·
 1977 11  527·
 1977 10  5310.
 1977 09  8812.
 1977 08  7118·
 1977 07  731·
 1977 06  4318·
 1977 05  5012·
 1977 04  177·
 1977 03  836·
 1977 02  851.
 1977 01  395·
 1976 12 371.
 1976 11 741.
 1976 10 57.
 1976 09 1313.
 1976 08 1821·
 1976 07 024·
 1976 06 5214.
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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

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







      Example 3: Get Population Level Data for Workers





 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 16-17 years, 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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