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 Series Title: Employment Level: Agriculture and Related Industries, Mexican Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1990 01 4645.
 1990 02 9027·
 1990 03 7049·
 1990 04 5962·
 1990 05 5253.
 1990 06 4691.
 1990 07 4277.
 1990 08 6988.
 1990 09 3784·
 1990 10 1467·
 1990 11 2733·
 1990 12 8934.
 1991 01  5035·
 1991 02  7448·
 1991 03  3941.
 1991 04  6630·
 1991 05  6959.
 1991 06  3396.
 1991 07  1458.
 1991 08  6692.
 1991 09  9369·
 1991 10  2470·
 1991 11  1739·
 1991 12  8527.
 1992 01 4731·
 1992 02 240.
 1992 03 3558.
 1992 04 4257.
 1992 05 8153·
 1992 06 4977·
 1992 07 8159.
 1992 08 8161.
 1992 09 7266.
 1992 10 7137.
 1992 11 9246·
 1992 12 7141.
 1993 01  2042.
 1993 02  228·
 1993 03  3239.
 1993 04  646·
 1993 05  4949.
 1993 06  9656·
 1993 07  8960·
 1993 08  559.
 1993 09  1161·
 1993 10  3648·
 1993 11  7564.
 1993 12  1351.
 1994 01 8147.
 1994 02 2947·
 1994 03 2841.
 1994 04 9851.
 1994 05 5968.
 1994 06 577·
 1994 07 1185·
 1994 08 5598·
 1994 09 7071·
 1994 10 2255·
 1994 11 1349·
 1994 12 347·
 1995 01  6532·
 1995 02  6237.
 1995 03  4661.
 1995 04  8661·
 1995 05  1987·
 1995 06  3093·
 1995 07  4785·
 1995 08  7286·
 1995 09  3482.
 1995 10  5978.
 1995 11  8061·
 1995 12  5856·
 1996 01 3350.
 1996 02 573·
 1996 03 3370·
 1996 04 6055.
 1996 05 6856.
 1996 06 5084.
 1996 07 1980·
 1996 08 2476.
 1996 09 1365.
 1996 10 161.
 1996 11 7566.
 1996 12 1944.
 1997 01  7060.
 1997 02  8947·
 1997 03  6443.
 1997 04  3979.
 1997 05  6482·
 1997 06  7084·
 1997 07  74115·
 1997 08  3115·
 1997 09  44112·
 1997 10  2779·
 1997 11  1975·
 1997 12  5469·
 1998 01 8768·
 1998 02 6686.
 1998 03 3570.
 1998 04 6375.
 1998 05 9386·
 1998 06 1965.
 1998 07 8784·
 1998 08 24146·
 1998 09 87128.
 1998 10 4289·
 1998 11 6158·
 1998 12 5540.
 1999 01  2067·
 1999 02  1763.
 1999 03  7151·
 1999 04  075·
 1999 05  6777.
 1999 06  50123·
 1999 07  54108.
 1999 08  30108·
 1999 09  2896.
 1999 10  7478·
 1999 11  7467.
 1999 12  3797·
 2000 01 2890·
 2000 02 4582.
 2000 03 1975·
 2000 04 4283.
 2000 05 1979·
 2000 06 4498·
 2000 07 077.
 2000 08 8890·
 2000 09 7654·
 2000 10 7964.
 2000 11 5763·
 2000 12 4464·
 2001 01  9886.
 2001 02  8059.
 2001 03  5155.
 2001 04  567.
 2001 05  12104.
 2001 06  566·
 2001 07  7249·
 2001 08  8968·
 2001 09  6864.
 2001 10  3585·
 2001 11  3169·
 2001 12  4156.
 2002 01 4084.
 2002 02 7671.
 2002 03 6761·
 2002 04 3067·
 2002 05 3199·
 2002 06 6185·
 2002 07 43116·
 2002 08 5072·
 2002 09 6497.
 2002 10 47106.
 2002 11 4663·
 2002 12 2157·
 2003 01  9058·
 2003 02  1367·
 2003 03  9080·
 2003 04  8572·
 2003 05  8584.
 2003 06  6883.
 2003 07  1182·
 2003 08  14114·
 2003 09  49114·
 2003 10  43120.
 2003 11  7490.
 2003 12  081·
 2004 01 869.
 2004 02 9549·
 2004 03 6648.
 2004 04 6269·
 2004 05 1175·
 2004 06 577.
 2004 07 076·
 2004 08 46117·
 2004 09 35101·
 2004 10 8097·
 2004 11 1493·
 2004 12 2044·
 2005 01  7949·
 2005 02  5143·
 2005 03  7056·
 2005 04  7848.
 2005 05  7066·
 2005 06  7572.
 2005 07  5774·
 2005 08  3997.
 2005 09  5688·
 2005 10  3476·
 2005 11  8874·
 2005 12  4847.
 2006 01 1553·
 2006 02 3551·
 2006 03 9944.
 2006 04 7381.
 2006 05 4680·
 2006 06 9118·
 2006 07 55100·
 2006 08 9112·
 2006 09 7475.
 2006 10 1262.
 2006 11 4448.
 2006 12 7552.
 2007 01  5145.
 2007 02  2765·
 2007 03  7772·
 2007 04  1563·
 2007 05  5057·
 2007 06  6090.
 2007 07  9382.
 2007 08  9954·
 2007 09  7468·
 2007 10  4262·
 2007 11  5549.
 2007 12  1967.
 2008 01 4664.
 2008 02 3147.
 2008 03 5163.
 2008 04 9771.
 2008 05 1961·
 2008 06 763.
 2008 07 9473.
 2008 08 7489.
 2008 09 6682·
 2008 10 79101·
 2008 11 2065.
 2008 12 2264·
 2009 01  8882.
 2009 02  7660.
 2009 03  9545.
 2009 04  3373.
 2009 05  1184·
 2009 06  5696·
 2009 07  499·
 2009 08  2896.
 2009 09  8679.
 2009 10  167.
 2009 11  6266.
 2009 12  4957·
 2010 01 8667.
 2010 02 1760.
 2010 03 651·
 2010 04 6753·
 2010 05 14115.
 2010 06 35118·
 2010 07 99120·
 2010 08 76117·
 2010 09 94109·
 2010 10 13115.
 2010 11 2898·
 2010 12 9473·
 2011 01  7681·
 2011 02  3285·
 2011 03  859·
 2011 04  6563.
 2011 05  3798·
 2011 06  99124.
 2011 07  75145.
 2011 08  60136·
 2011 09  76112.
 2011 10  4590·
 2011 11  9266·
 2011 12  7284·
 2012 01 1984.
 2012 02 2791·
 2012 03 4865.
 2012 04 2044·
 2012 05 1671·
 2012 06 2795.
 2012 07 55111.
 2012 08 48109·
 2012 09 43128.
 2012 10 51113.
 2012 11 5279·
 2012 12 2562·
 2013 01  047.
 2013 02  3153·
 2013 03  051.
 2013 04  4675·
 2013 05  1290.
 2013 06  2379·
 2013 07  89104.
 2013 08  3096.
 2013 09  30118.
 2013 10  9140·
 2013 11  30125·
 2013 12  2165.
 2014 01 2968·
 2014 02 9755·
 2014 03 6270.
 2014 04 88103.
 2014 05 10123·
 2014 06 16123·
 2014 07 48123·
 2014 08 25105·
 2014 09 98124·
 2014 10 25122·
 2014 11 75105.
 2014 12 5175·
 2015 01  4380·
 2015 02  578.
 2015 03  5791.
 2015 04  10127.
 2015 05  2079.
 2015 06  62108.
 2015 07  3193·
 2015 08  73118·
 2015 09  31135·
 2015 10  28133.
 2015 11  60118·
 2015 12  32114·
 2016 01 1106.
 2016 02 59122.
 2016 03 32109.
 2016 04 6104·
 2016 05 79107·
 2016 06 38119.
 2016 07 61130.
 2016 08 41158·
 2016 09 42160·
 2016 10 71135.
 2016 11 83124·
 2016 12 594.
 2017 01  8988.
 2017 02  9082.
 2017 03  62108·
 2017 04  92132·
 2017 05  47176.
 2017 06  50179.


 2017 07  85152·
 2017 08  22134·
 2017 09  65158·
 2017 10  35161.
 2017 11  67149·
 2017 12  38102.
 2018 01 1994·
 2018 02 50106.
 2018 03 43104.
 2018 04 1087·
 2018 05 9115·
 2018 06 27129·
 2018 07 78196.
 2018 08 31168·
 2018 09 60213·
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate and 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: Employment Level: Agriculture and Related Industries, Mexican 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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