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 Series Title: Employed: Wholesale and retail trade, Asian: 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 69901.
 2000 02 60883.
 2000 03 95775·
 2000 04 76809.
 2000 05 30840·
 2000 06 86829·
 2000 07 75904·
 2000 08 58943.
 2000 09 76882·
 2000 10 29856·
 2000 11 75822·
 2000 12 58862·
 2001 01  58884.
 2001 02  71915·
 2001 03  7861.
 2001 04  19864·
 2001 05  51899.
 2001 06  19860·
 2001 07  10892·
 2001 08  10890·
 2001 09  54901·
 2001 10  3898·
 2001 11  46869·
 2001 12  27826·
 2002 01 95789.
 2002 02 82818.
 2002 03 4752·
 2002 04 88843.
 2002 05 22768·
 2002 06 35836.
 2002 07 95970.
 2002 08 36976·
 2002 09 12926.
 2002 10 71965.
 2002 11 58907·
 2002 12 42875·
 2003 01  65793·
 2003 02  21761.
 2003 03  57704·
 2003 04  99773.
 2003 05  6831.
 2003 06  41896.
 2003 07  78987.
 2003 08  27932.
 2003 09  85913·
 2003 10  12797.
 2003 11  35893.
 2003 12  70997.
 2004 01 79940.
 2004 02 43857·
 2004 03 65835·
 2004 04 96810.
 2004 05 87855.
 2004 06 64952.
 2004 07 32945·
 2004 08 0977.
 2004 09 34854.
 2004 10 31851·
 2004 11 23880.
 2004 12 2888.
 2005 01  72925·
 2005 02  28977·
 2005 03  511039.
 2005 04  44936·
 2005 05  76905·
 2005 06  59902·
 2005 07  55914.
 2005 08  98910·
 2005 09  45878.
 2005 10  57881·
 2005 11  97885·
 2005 12  55871.
 2006 01 6887.
 2006 02 79900.
 2006 03 64893·
 2006 04 36857.
 2006 05 8877·
 2006 06 6836.
 2006 07 70874.
 2006 08 85893.
 2006 09 28900·
 2006 10 44906.
 2006 11 53919.
 2006 12 71971.
 2007 01  65895.
 2007 02  26969.
 2007 03  76955·
 2007 04  88951·
 2007 05  45922.
 2007 06  8878·
 2007 07  26823·
 2007 08  56855.
 2007 09  18847·
 2007 10  72942·
 2007 11  161048.
 2007 12  171015·
 2008 01 60988·
 2008 02 24874·
 2008 03 85831.
 2008 04 42884.
 2008 05 71787.
 2008 06 95810.
 2008 07 94854·
 2008 08 25878·
 2008 09 76919·
 2008 10 44975·
 2008 11 331016.
 2008 12 85970.
 2009 01  27889·
 2009 02  51942.
 2009 03  14894.
 2009 04  65925·
 2009 05  97995·
 2009 06  22994.
 2009 07  74978·
 2009 08  36928·
 2009 09  88938·
 2009 10  90935·
 2009 11  78900.
 2009 12  91856·
 2010 01 26805·
 2010 02 12815·
 2010 03 12817.
 2010 04 49907.
 2010 05 59887·
 2010 06 68913·
 2010 07 891028.
 2010 08 541010.
 2010 09 65976·
 2010 10 65942·
 2010 11 48953·
 2010 12 77874·
 2011 01  42789.
 2011 02  36867·
 2011 03  51832·
 2011 04  10893·
 2011 05  18956·
 2011 06  361003.
 2011 07  86933.
 2011 08  73884.
 2011 09  41869.
 2011 10  48900·
 2011 11  66908·
 2011 12  10889.
 2012 01 881004·
 2012 02 771005·
 2012 03 29957.
 2012 04 90909.
 2012 05 58965·
 2012 06 571064.
 2012 07 381023·
 2012 08 71069·
 2012 09 771080·
 2012 10 42989.
 2012 11 81979·
 2012 12 811122·
 2013 01  961042.
 2013 02  161080·
 2013 03  70986·
 2013 04  56967.
 2013 05  901020·
 2013 06  841071·
 2013 07  441062.
 2013 08  11063.
 2013 09  601026.
 2013 10  78962.
 2013 11  651033.
 2013 12  91178·
 2014 01 301104·
 2014 02 551216.
 2014 03 211174.
 2014 04 01076.
 2014 05 511099.
 2014 06 971109.
 2014 07 261148·
 2014 08 191134.
 2014 09 991035·
 2014 10 9987.
 2014 11 171052.
 2014 12 331129.
 2015 01  731116.
 2015 02  251250.
 2015 03  561260.
 2015 04  391237.
 2015 05  01223.
 2015 06  01214·
 2015 07  331200·
 2015 08  541166.
 2015 09  291079.
 2015 10  161007.
 2015 11  591013·
 2015 12  221061.
 2016 01 371067·
 2016 02 791209·
 2016 03 731281·
 2016 04 141278·
 2016 05 231171.
 2016 06 221218·
 2016 07 371234.
 2016 08 221082.
 2016 09 131143·
 2016 10 11189·
 2016 11 401171·
 2016 12 671270.
 2017 01  571224·
 2017 02  981127·
 2017 03  941200.
 2017 04  921206·
 2017 05  301230·
 2017 06  181244.
 2017 07  381196.
 2017 08  661235·
 2017 09  341169.
 2017 10  951208.
 2017 11  331156.


 2017 12  841137·
 2018 01 931119·
 2018 02 841049.
 2018 03 681044.
 2018 04 651113.
 2018 05 581173.
 2018 06 681216·
 2018 07 561173·
 2018 08 531156·
 2018 09 41084.
 2018 10 521110.
 2018 11 351177·
 2018 12 161111.
 2019 01  321045·
 2019 02  681096.
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Similar Series

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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: Employed: Wholesale and retail trade, Asian: 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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