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 Series Title: Women, employed government wage and salary workers in Retail trade: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2000 01 1946.
 2000 02 5748.
 2000 03 543·
 2000 04 1434·
 2000 05 6219.
 2000 06 2834·
 2000 07 9237·
 2000 08 6638·
 2000 09 4041.
 2000 10 6529.
 2000 11 4932·
 2000 12 8539·
 2001 01  433.
 2001 02  5245·
 2001 03  8854·
 2001 04  1553·
 2001 05  2936·
 2001 06  9430·
 2001 07  4830·
 2001 08  2783·
 2001 09  1458.
 2001 10  2337.
 2001 11  9130.
 2001 12  1335.
 2002 01 8735.
 2002 02 9640.
 2002 03 639.
 2002 04 9326·
 2002 05 9633·
 2002 06 9438.
 2002 07 446.
 2002 08 1157.
 2002 09 1850·
 2002 10 2478.
 2002 11 2460.
 2002 12 3660·
 2003 01  5353.
 2003 02  1925.
 2003 03  3019.
 2003 04  6323.
 2003 05  2626·
 2003 06  3320·
 2003 07  836.
 2003 08  1131.
 2003 09  8839.
 2003 10  4958·
 2003 11  7235.
 2003 12  2345·
 2004 01 1346·
 2004 02 7421·
 2004 03 5937.
 2004 04 6931·
 2004 05 362.
 2004 06 4046·
 2004 07 3357·
 2004 08 4245.
 2004 09 8342·
 2004 10 254·
 2004 11 8156·
 2004 12 6353.
 2005 01  361.
 2005 02  4345·
 2005 03  1740.
 2005 04  7552·
 2005 05  3852.
 2005 06  6854·
 2005 07  7755·
 2005 08  4865·
 2005 09  8952·
 2005 10  1154·
 2005 11  2646.
 2005 12  7537.
 2006 01 8242.
 2006 02 2745.
 2006 03 5047.
 2006 04 7635.
 2006 05 6740·
 2006 06 9923.
 2006 07 6430·
 2006 08 9438.
 2006 09 1872.
 2006 10 3273·
 2006 11 473.
 2006 12 084.
 2007 01  3761.
 2007 02  5854.
 2007 03  3352·
 2007 04  8763·
 2007 05  4965·
 2007 06  3557.
 2007 07  4054·
 2007 08  7355·
 2007 09  545·
 2007 10  4331.
 2007 11  3754.
 2007 12  545.
 2008 01 7951.
 2008 02 8958.
 2008 03 6371·
 2008 04 4959·
 2008 05 7262.
 2008 06 677·
 2008 07 8064·
 2008 08 260·
 2008 09 967.
 2008 10 4969·
 2008 11 7653.
 2008 12 8177·
 2009 01  4149·
 2009 02  050.
 2009 03  6346·
 2009 04  3136.
 2009 05  4440.
 2009 06  6651.
 2009 07  8144·
 2009 08  2156·
 2009 09  1758·
 2009 10  7972.
 2009 11  9154.
 2009 12  4556.
 2010 01 8754·
 2010 02 9549.
 2010 03 8265·
 2010 04 2358.
 2010 05 277·
 2010 06 9579·
 2010 07 6757·
 2010 08 9838.
 2010 09 4047·
 2010 10 8772.
 2010 11 8263·
 2010 12 4055.
 2011 01  9949.
 2011 02  225.
 2011 03  9230·
 2011 04  4247.
 2011 05  739·
 2011 06  9746·
 2011 07  8445.
 2011 08  2567·
 2011 09  1261.
 2011 10  5346.
 2011 11  7246.
 2011 12  3134·
 2012 01 9136·
 2012 02 7845·
 2012 03 9253.
 2012 04 3148.
 2012 05 4326.
 2012 06 164.
 2012 07 867.
 2012 08 1848·
 2012 09 9559·
 2012 10 8166·
 2012 11 775·
 2012 12 1255·
 2013 01  9654·
 2013 02  032·
 2013 03  434·
 2013 04  5655·
 2013 05  2264·
 2013 06  6236.
 2013 07  3553·
 2013 08  2033.
 2013 09  7347·
 2013 10  145·
 2013 11  6366.
 2013 12  9861.
 2014 01 7561·
 2014 02 7358.
 2014 03 7646·
 2014 04 837.
 2014 05 7851·
 2014 06 5924·
 2014 07 8842·
 2014 08 9745.
 2014 09 5849·
 2014 10 6657.
 2014 11 3655·
 2014 12 3146·
 2015 01  1438·
 2015 02  2649.
 2015 03  8255·
 2015 04  666.
 2015 05  7344·
 2015 06  9562·
 2015 07  1654·
 2015 08  4052·
 2015 09  8563·
 2015 10  5629.
 2015 11  4940·
 2015 12  7823·
 2016 01 2458·
 2016 02 1467·
 2016 03 2059·
 2016 04 8954·
 2016 05 9239.
 2016 06 140·
 2016 07 9242·
 2016 08 6758.
 2016 09 1454·
 2016 10 7534.
 2016 11 5164·
 2016 12 3248.
 2017 01  4047.
 2017 02  1650.
 2017 03  1336.
 2017 04  2639.
 2017 05  4651·
 2017 06  3144·


 2017 07  1340·
 2017 08  2050.
 2017 09  3242·
 2017 10  5231·
 2017 11  1546·
 2017 12  854.
 2018 01 2355.
 2018 02 3635.
 2018 03 845.
 2018 04 841.
 2018 05 7031·
 2018 06 6421.
 2018 07 342.
 2018 08 6551.
 2018 09 4831·
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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: Women, employed government wage and salary workers in Retail trade: 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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