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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 5446.
 2000 02 1048.
 2000 03 6943.
 2000 04 5634.
 2000 05 2419·
 2000 06 2734.
 2000 07 2137·
 2000 08 9238·
 2000 09 541·
 2000 10 8629·
 2000 11 1832.
 2000 12 7039·
 2001 01  4733.
 2001 02  6945·
 2001 03  7354·
 2001 04  3453·
 2001 05  2436·
 2001 06  8330.
 2001 07  2330·
 2001 08  5483.
 2001 09  3758·
 2001 10  5837.
 2001 11  3130·
 2001 12  2435·
 2002 01 1335.
 2002 02 5340.
 2002 03 8639·
 2002 04 6326·
 2002 05 033·
 2002 06 4738.
 2002 07 9946·
 2002 08 1657·
 2002 09 7450·
 2002 10 4978.
 2002 11 1060.
 2002 12 5060·
 2003 01  3753·
 2003 02  9025·
 2003 03  8119·
 2003 04  6123·
 2003 05  1326·
 2003 06  2620.
 2003 07  9936.
 2003 08  6731·
 2003 09  5239.
 2003 10  3958.
 2003 11  7835.
 2003 12  1345.
 2004 01 3046.
 2004 02 3521·
 2004 03 5637·
 2004 04 6831·
 2004 05 4862·
 2004 06 4746·
 2004 07 9557.
 2004 08 2645.
 2004 09 3042.
 2004 10 3154·
 2004 11 8356.
 2004 12 653·
 2005 01  2861·
 2005 02  6845·
 2005 03  3440.
 2005 04  5252.
 2005 05  1652·
 2005 06  6554·
 2005 07  8555·
 2005 08  3465·
 2005 09  9552.
 2005 10  5454.
 2005 11  9946·
 2005 12  4537·
 2006 01 9142·
 2006 02 9245.
 2006 03 6347·
 2006 04 435·
 2006 05 5340.
 2006 06 6023.
 2006 07 9230.
 2006 08 5738·
 2006 09 5772.
 2006 10 6473.
 2006 11 2273·
 2006 12 7184.
 2007 01  461·
 2007 02  3754·
 2007 03  1752·
 2007 04  4263.
 2007 05  1965·
 2007 06  3557·
 2007 07  6454.
 2007 08  8855·
 2007 09  5245·
 2007 10  4031·
 2007 11  7754·
 2007 12  5345·
 2008 01 7951.
 2008 02 5858.
 2008 03 9371.
 2008 04 759.
 2008 05 9962.
 2008 06 2177.
 2008 07 7564·
 2008 08 4360.
 2008 09 4067.
 2008 10 8569.
 2008 11 1153.
 2008 12 8177.
 2009 01  5049·
 2009 02  3350.
 2009 03  1446·
 2009 04  6536·
 2009 05  540·
 2009 06  7151.
 2009 07  2144.
 2009 08  6456.
 2009 09  658.
 2009 10  3072.
 2009 11  9754·
 2009 12  7256·
 2010 01 7854.
 2010 02 6749.
 2010 03 2865.
 2010 04 958·
 2010 05 7177.
 2010 06 6479.
 2010 07 2857.
 2010 08 1838·
 2010 09 6247.
 2010 10 2872·
 2010 11 3463·
 2010 12 6955.
 2011 01  4949.
 2011 02  8925.
 2011 03  930.
 2011 04  5647·
 2011 05  5939.
 2011 06  646·
 2011 07  4145.
 2011 08  9767.
 2011 09  4261·
 2011 10  5846.
 2011 11  4446·
 2011 12  3834.
 2012 01 7336.
 2012 02 5445.
 2012 03 5453.
 2012 04 4648·
 2012 05 5426.
 2012 06 2464.
 2012 07 3567.
 2012 08 1748.
 2012 09 859.
 2012 10 2666.
 2012 11 7575.
 2012 12 7055.
 2013 01  8754.
 2013 02  4032.
 2013 03  8734·
 2013 04  4855·
 2013 05  6564.
 2013 06  7436.
 2013 07  853·
 2013 08  2133·
 2013 09  4447·
 2013 10  6045.
 2013 11  166.
 2013 12  8361·
 2014 01 4961·
 2014 02 5358.
 2014 03 5546.
 2014 04 5337.
 2014 05 3051.
 2014 06 3524·
 2014 07 8242.
 2014 08 7545·
 2014 09 6349·
 2014 10 1457·
 2014 11 2055·
 2014 12 1846.
 2015 01  4738.
 2015 02  2149.
 2015 03  3255.
 2015 04  7766.
 2015 05  844·
 2015 06  1262·
 2015 07  654.
 2015 08  7052·
 2015 09  9863·
 2015 10  6829·
 2015 11  5440.
 2015 12  4223.
 2016 01 9058.
 2016 02 9867.
 2016 03 1559·
 2016 04 6254.
 2016 05 8639·
 2016 06 3240·
 2016 07 5242·
 2016 08 2458.
 2016 09 1054.
 2016 10 2734.
 2016 11 5264·
 2016 12 4848.
 2017 01  1447·
 2017 02  6550.
 2017 03  2836.
 2017 04  7639.
 2017 05  7251.
 2017 06  5144·
 2017 07  1940.
 2017 08  7950·
 2017 09  8642·
 2017 10  1931.
 2017 11  8646·


 2017 12  5154.
 2018 01 8055·
 2018 02 2435·
 2018 03 1945·
 2018 04 1041.
 2018 05 431.
 2018 06 4921·
 2018 07 3042·
 2018 08 151·
 2018 09 3531.
 2018 10 9943·
 2018 11 5628.
 2018 12 9332·
 2019 01  7241·
 2019 02  635.
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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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