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 Series Title: Employed: Education and health services, Hispanic or Latino: 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 622119.
 2000 02 382169.
 2000 03 192182·
 2000 04 452084.
 2000 05 822026·
 2000 06 941973.
 2000 07 511880·
 2000 08 521968.
 2000 09 742106.
 2000 10 552118·
 2000 11 912209·
 2000 12 632169·
 2001 01  892213.
 2001 02  22172·
 2001 03  502170·
 2001 04  232170.
 2001 05  22180·
 2001 06  422185.
 2001 07  682184.
 2001 08  12225·
 2001 09  142184.
 2001 10  72276·
 2001 11  62281·
 2001 12  912470·
 2002 01 512417·
 2002 02 532371.
 2002 03 532398·
 2002 04 132370.
 2002 05 622441.
 2002 06 622381.
 2002 07 212339·
 2002 08 112388.
 2002 09 222438·
 2002 10 412443·
 2002 11 502479·
 2002 12 542522.
 2003 01  332656·
 2003 02  212538.
 2003 03  02520·
 2003 04  352513.
 2003 05  202514·
 2003 06  582493·
 2003 07  612413.
 2003 08  742402.
 2003 09  332420.
 2003 10  362375·
 2003 11  452253·
 2003 12  162376·
 2004 01 482374·
 2004 02 592421·
 2004 03 902651·
 2004 04 292614.
 2004 05 642770.
 2004 06 602754·
 2004 07 592729·
 2004 08 72619·
 2004 09 82660·
 2004 10 952652·
 2004 11 392551·
 2004 12 702633.
 2005 01  292558.
 2005 02  472559.
 2005 03  452635·
 2005 04  622543·
 2005 05  32602.
 2005 06  212532·
 2005 07  132562·
 2005 08  512735·
 2005 09  312652·
 2005 10  492778.
 2005 11  72743·
 2005 12  332669.
 2006 01 372704·
 2006 02 892748·
 2006 03 142740·
 2006 04 262662.
 2006 05 732704·
 2006 06 212545.
 2006 07 472539·
 2006 08 742594·
 2006 09 142715·
 2006 10 522940·
 2006 11 452887·
 2006 12 462840·
 2007 01  592858·
 2007 02  142868.
 2007 03  702956·
 2007 04  373008·
 2007 05  353029.
 2007 06  642885·
 2007 07  92885·
 2007 08  662922·
 2007 09  922897·
 2007 10  833001.
 2007 11  773034.
 2007 12  772992·
 2008 01 53077·
 2008 02 783071·
 2008 03 103051·
 2008 04 383066·
 2008 05 742993.
 2008 06 802896·
 2008 07 722801·
 2008 08 452978.
 2008 09 253084.
 2008 10 463066·
 2008 11 503203·
 2008 12 163192·
 2009 01  93152.
 2009 02  583301·
 2009 03  583248·
 2009 04  963309·
 2009 05  13283·
 2009 06  232951·
 2009 07  332981.
 2009 08  532919.
 2009 09  03099.
 2009 10  713208.
 2009 11  393363·
 2009 12  823290·
 2010 01 333360·
 2010 02 603375·
 2010 03 623317.
 2010 04 13310·
 2010 05 503356·
 2010 06 713236·
 2010 07 173088.
 2010 08 563151.
 2010 09 273309.
 2010 10 123443·
 2010 11 403486.
 2010 12 153431.
 2011 01  633322.
 2011 02  123335·
 2011 03  953381·
 2011 04  723422.
 2011 05  843423·
 2011 06  313409·
 2011 07  703286·
 2011 08  463246.
 2011 09  403348·
 2011 10  473285.
 2011 11  773356·
 2011 12  823326·
 2012 01 83532·
 2012 02 703590.
 2012 03 553650.
 2012 04 493692·
 2012 05 873684.
 2012 06 293678·
 2012 07 663621·
 2012 08 413669.
 2012 09 23769·
 2012 10 833788.
 2012 11 993719·
 2012 12 763717·
 2013 01  53676·
 2013 02  123675.
 2013 03  653663·
 2013 04  03614·
 2013 05  703716.
 2013 06  223725·
 2013 07  33807·
 2013 08  813678.
 2013 09  973676·
 2013 10  473669·
 2013 11  773616·
 2013 12  133684·
 2014 01 133714·
 2014 02 423695.
 2014 03 733766·
 2014 04 163811·
 2014 05 683712.
 2014 06 893717.
 2014 07 53645·
 2014 08 333680.
 2014 09 363909·
 2014 10 943884.
 2014 11 103862.
 2014 12 353807.
 2015 01  193671·
 2015 02  903730.
 2015 03  523877·
 2015 04  143889.
 2015 05  424175·
 2015 06  334098·
 2015 07  183821·
 2015 08  903825·
 2015 09  553962.
 2015 10  43981·
 2015 11  213985·
 2015 12  83952·
 2016 01 334059·
 2016 02 104143.
 2016 03 04110·
 2016 04 364300·
 2016 05 774291·
 2016 06 834229.
 2016 07 163962·
 2016 08 694056.
 2016 09 134100.
 2016 10 804106.
 2016 11 594179.
 2016 12 254254·
 2017 01  914090·
 2017 02  824323.
 2017 03  404309·
 2017 04  494345·


 2017 05  854349.
 2017 06  954534·
 2017 07  984377.
 2017 08  104263·
 2017 09  974325·
 2017 10  524454.
 2017 11  964531·
 2017 12  24392.
 2018 01 524551·
 2018 02 94564·
 2018 03 214446·
 2018 04 444573.
 2018 05 04558·
 2018 06 484625.
 2018 07 864538·
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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: Education and health services, Hispanic or Latino: 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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