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 Series Title: Employment Level: Professional, and Related Occupations in Retail Trade Industry: 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 38841·
 2000 02 10825·
 2000 03 58748.
 2000 04 74680.
 2000 05 72683·
 2000 06 68802.
 2000 07 80794.
 2000 08 58850.
 2000 09 29897.
 2000 10 81796.
 2000 11 60803.
 2000 12 96780·
 2001 01  59776·
 2001 02  31778.
 2001 03  9746·
 2001 04  33792.
 2001 05  37784·
 2001 06  23724·
 2001 07  66841.
 2001 08  39807·
 2001 09  64779·
 2001 10  90789.
 2001 11  94705·
 2001 12  7691·
 2002 01 65760.
 2002 02 89792·
 2002 03 81795·
 2002 04 56769.
 2002 05 91803.
 2002 06 0746·
 2002 07 40792.
 2002 08 31784·
 2002 09 17723.
 2002 10 31753·
 2002 11 8758·
 2002 12 1758.
 2003 01  43787·
 2003 02  13804.
 2003 03  48789.
 2003 04  60794·
 2003 05  94790.
 2003 06  3767·
 2003 07  48841·
 2003 08  27820.
 2003 09  22843·
 2003 10  83820.
 2003 11  22822·
 2003 12  46798·
 2004 01 1764.
 2004 02 58851·
 2004 03 7839.
 2004 04 86818.
 2004 05 32793.
 2004 06 62761·
 2004 07 66781·
 2004 08 41723.
 2004 09 41755·
 2004 10 50808.
 2004 11 87860·
 2004 12 32893.
 2005 01  77816.
 2005 02  3864·
 2005 03  82835.
 2005 04  1807.
 2005 05  16862.
 2005 06  30822·
 2005 07  90846·
 2005 08  18803·
 2005 09  59780.
 2005 10  61797.
 2005 11  73777.
 2005 12  77846·
 2006 01 30772·
 2006 02 53765.
 2006 03 20740.
 2006 04 97787.
 2006 05 81858.
 2006 06 87814·
 2006 07 44838·
 2006 08 22823·
 2006 09 86850.
 2006 10 71836·
 2006 11 81889·
 2006 12 22856·
 2007 01  46748·
 2007 02  35766.
 2007 03  96789·
 2007 04  90798.
 2007 05  87807.
 2007 06  37872.
 2007 07  75829·
 2007 08  46776·
 2007 09  59819·
 2007 10  58776·
 2007 11  32881.
 2007 12  34952·
 2008 01 36885·
 2008 02 5870·
 2008 03 6848·
 2008 04 23856·
 2008 05 21838.
 2008 06 10810·
 2008 07 57827.
 2008 08 8771·
 2008 09 37780.
 2008 10 29805.
 2008 11 76818.
 2008 12 6884·
 2009 01  35872·
 2009 02  43836.
 2009 03  73809·
 2009 04  63802·
 2009 05  92789.
 2009 06  60814·
 2009 07  88825.
 2009 08  47846.
 2009 09  6795.
 2009 10  10790.
 2009 11  84794·
 2009 12  54831.
 2010 01 4829.
 2010 02 52841.
 2010 03 47902.
 2010 04 1910·
 2010 05 36833.
 2010 06 65799.
 2010 07 91773·
 2010 08 33789·
 2010 09 77774.
 2010 10 58824·
 2010 11 54807.
 2010 12 19738·
 2011 01  28780·
 2011 02  61830·
 2011 03  99848.
 2011 04  53838·
 2011 05  14864·
 2011 06  32810.
 2011 07  14803·
 2011 08  55809·
 2011 09  86754·
 2011 10  51787·
 2011 11  11812·
 2011 12  68822.
 2012 01 18879.
 2012 02 26824.
 2012 03 29783·
 2012 04 62787·
 2012 05 12796·
 2012 06 88841·
 2012 07 30807·
 2012 08 31842·
 2012 09 92896·
 2012 10 93907.
 2012 11 2958.
 2012 12 94940.
 2013 01  9807.
 2013 02  24839.
 2013 03  58838·
 2013 04  95798.
 2013 05  39864·
 2013 06  88838·
 2013 07  36767·
 2013 08  3824.
 2013 09  81827.
 2013 10  14922·
 2013 11  0956.
 2013 12  13945.
 2014 01 62850.
 2014 02 62798·
 2014 03 36861.
 2014 04 43933.
 2014 05 32992.
 2014 06 11976.
 2014 07 57960.
 2014 08 38939·
 2014 09 65924.
 2014 10 691033.
 2014 11 21094·
 2014 12 671005.
 2015 01  63961·
 2015 02  67870.
 2015 03  34867.
 2015 04  23825·
 2015 05  50909·
 2015 06  62964.
 2015 07  40970.
 2015 08  271014.
 2015 09  78938·
 2015 10  35942.
 2015 11  33991·
 2015 12  221020.
 2016 01 21953.
 2016 02 94991·
 2016 03 521006·
 2016 04 78985.
 2016 05 80980.
 2016 06 70992.
 2016 07 581036.
 2016 08 87976.
 2016 09 81910·
 2016 10 19976.
 2016 11 40969.
 2016 12 71970.
 2017 01  731020.
 2017 02  231044.
 2017 03  11994.
 2017 04  721030·


 2017 05  331079·
 2017 06  891068·
 2017 07  9971·
 2017 08  61934·
 2017 09  59989·
 2017 10  481056.
 2017 11  971126·
 2017 12  301118·
 2018 01 791038·
 2018 02 57981.
 2018 03 611054.
 2018 04 01016·
 2018 05 421052.
 2018 06 981035·
 2018 07 171068·
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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: Professional, and Related Occupations in Retail Trade Industry: 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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