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 Series Title: Employment Level: Agriculture and Related Industries, 20 years and over, Mexican Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 9640·
 2012 03 462.
 2012 02 3388.
 2012 01 4184·
 2011 12  1284.
 2011 11  3166·
 2011 10  8490·
 2011 09  90112·
 2011 08  45136·
 2011 07  6141.
 2011 06  87121.
 2011 05  8798.
 2011 04  4563.
 2011 03  1159.
 2011 02  5383·
 2011 01  7781.
 2010 12 8773·
 2010 11 5396.
 2010 10 20110·
 2010 09 29105·
 2010 08 71114.
 2010 07 64118.
 2010 06 53113·
 2010 05 37115·
 2010 04 2353.
 2010 03 9951·
 2010 02 3760.
 2010 01 2066·
 2009 12  9454.
 2009 11  4162.
 2009 10  8762.
 2009 09  2371·
 2009 08  5894.
 2009 07  9790·
 2009 06  4190·
 2009 05  1481.
 2009 04  1671·
 2009 03  9745·
 2009 02  6060.
 2009 01  8882.
 2008 12 9464·
 2008 11 9965·
 2008 10 34101.
 2008 09 6482·
 2008 08 4286·
 2008 07 8470.
 2008 06 7460·
 2008 05 8561.
 2008 04 3468.
 2008 03 6060.
 2008 02 2043.
 2008 01 2258.
 2007 12  7364·
 2007 11  5649.
 2007 10  3362·
 2007 09  6862.
 2007 08  8251·
 2007 07  3175.
 2007 06  178.
 2007 05  4257·
 2007 04  1359·
 2007 03  6666.
 2007 02  3861·
 2007 01  8845·
 2006 12 4149.
 2006 11 6745.
 2006 10 8262.
 2006 09 7775.
 2006 08 66104.
 2006 07 6690·
 2006 06 95118·
 2006 05 180·
 2006 04 1477.
 2006 03 1941.
 2006 02 6451·
 2006 01 8052.
 2005 12  3446·
 2005 11  1070·
 2005 10  472.
 2005 09  5878·
 2005 08  388·
 2005 07  4372.
 2005 06  5272.
 2005 05  466.
 2005 04  2146·
 2005 03  5154.
 2005 02  7140.
 2005 01  1349·
 2004 12 1243.
 2004 11 9090·
 2004 10 4897·
 2004 09 3101·
 2004 08 29111·
 2004 07 4268.
 2004 06 9771.
 2004 05 1872·
 2004 04 4564.
 2004 03 1346·
 2004 02 5645.
 2004 01 2961·
 2003 12  6169·
 2003 11  3675·
 2003 10  87114·
 2003 09  28109·
 2003 08  4110·
 2003 07  6782.
 2003 06  7883.
 2003 05  3584·
 2003 04  2272·
 2003 03  8779·
 2003 02  4366.
 2003 01  9557·
 2002 12 9256.
 2002 11 363·
 2002 10 18106·
 2002 09 7693·
 2002 08 1470·
 2002 07 47109.
 2002 06 6782.
 2002 05 7293.
 2002 04 1365.
 2002 03 7559.
 2002 02 7970.
 2002 01 376·
 2001 12  4050·
 2001 11  7066.
 2001 10  6585·
 2001 09  1262.
 2001 08  6964.
 2001 07  3747·
 2001 06  6358.
 2001 05  7098.
 2001 04  361·
 2001 03  841·
 2001 02  3859.
 2001 01  7086·
 2000 12 6564.
 2000 11 4161·
 2000 10 7558·
 2000 09 3052·
 2000 08 675.
 2000 07 1674.
 2000 06 8995.
 2000 05 9676·
 2000 04 274·
 2000 03 4065·
 2000 02 1778.
 2000 01 3790.
 1999 12  5397.
 1999 11  4564·
 1999 10  2270·
 1999 09  4690·
 1999 08  84100·
 1999 07  88102·
 1999 06  92119.
 1999 05  4372·
 1999 04  4671.
 1999 03  5048·
 1999 02  4061.
 1999 01  7164·
 1998 12 1540.
 1998 11 3853.
 1998 10 484·
 1998 09 1108·
 1998 08 89129·
 1998 07 8384·
 1998 06 4661.
 1998 05 2675.
 1998 04 9672·
 1998 03 4270·
 1998 02 5586.
 1998 01 6565·
 1997 12  8566.
 1997 11  9776.
 1997 10  4479·
 1997 09  62101.
 1997 08  32103·
 1997 07  54108.
 1997 06  4980·
 1997 05  8783.
 1997 04  3772.
 1997 03  4635.
 1997 02  3543·
 1997 01  3452·
 1996 12 2643·
 1996 11 2861.
 1996 10 8959.
 1996 09 2261·
 1996 08 4976.
 1996 07 8276.
 1996 06 2478·
 1996 05 9457.
 1996 04 8055·
 1996 03 1567.
 1996 02 7873.
 1996 01 2147.
 1995 12  2253·
 1995 11  5959·
 1995 10  1371.
 1995 09  9678.
 1995 08  9976·
 1995 07  7066·
 1995 06  1986·
 1995 05  3982.
 1995 04  6160·
 1995 03  3061·
 1995 02  637·
 1995 01  9332·
 1994 12 8448.
 1994 11 4548.
 1994 10 1555·
 1994 09 2768·
 1994 08 6879.
 1994 07 4881.
 1994 06 665.
 1994 05 3761·
 1994 04 3951·
 1994 03 9437.
 1994 02 6946·
 1994 01 4045·
 1993 12  4748.
 1993 11  6658·
 1993 10  1648.
 1993 09  8260.
 1993 08  6753.
 1993 07  7056.
 1993 06  8550.
 1993 05  3143·
 1993 04  041.
 1993 03  3735.
 1993 02  3926.
 1993 01  8141.
 1992 12 7239.
 1992 11 2539·
 1992 10 6536·
 1992 09 5257·
 1992 08 3241.
 1992 07 1549·
 1992 06 7873·
 1992 05 8751·
 1992 04 5654.
 1992 03 1355.
 1992 02 1337.
 1992 01 5731·
 1991 12  4426·
 1991 11  5239·
 1991 10  3666·
 1991 09  5468·
 1991 08  2277.
 1991 07  8842.
 1991 06  3278.
 1991 05  9851·
 1991 04  4028.
 1991 03  238·
 1991 02  1646.
 1991 01  3433.
 1990 12 7433·
 1990 11 132.
 1990 10 2561.
 1990 09 3084.
 1990 08 2479·
 1990 07 1770·
 1990 06 2279·
 1990 05 8045·
 1990 04 1559.
 1990 03 746·
 1990 02 9527.
 1990 01 539.
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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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 Series Title: Employment Level: Agriculture and Related Industries, 20 years and over, 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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