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 Series Title: Employment Level: Mexican, Education, Training, and Library Occupations: 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 0307.
 2000 02 99288·
 2000 03 92305.
 2000 04 13262·
 2000 05 20283·
 2000 06 74271.
 2000 07 35248.
 2000 08 97271·
 2000 09 33286.
 2000 10 72246.
 2000 11 4247.
 2000 12 5271.
 2001 01  87298·
 2001 02  75306·
 2001 03  12339.
 2001 04  81331·
 2001 05  58316·
 2001 06  90309·
 2001 07  97309.
 2001 08  93295.
 2001 09  46316·
 2001 10  49278·
 2001 11  21230.
 2001 12  37276.
 2002 01 78269.
 2002 02 7300·
 2002 03 72307·
 2002 04 31274.
 2002 05 3276.
 2002 06 48274·
 2002 07 64277·
 2002 08 19322·
 2002 09 96349.
 2002 10 76356.
 2002 11 34342.
 2002 12 71329·
 2003 01  59347·
 2003 02  25291.
 2003 03  46279.
 2003 04  80298·
 2003 05  16306·
 2003 06  50301·
 2003 07  86250·
 2003 08  66316·
 2003 09  18304·
 2003 10  33335·
 2003 11  68336·
 2003 12  73312·
 2004 01 40275.
 2004 02 81264.
 2004 03 30291.
 2004 04 70351.
 2004 05 83403.
 2004 06 26356.
 2004 07 35341·
 2004 08 52295.
 2004 09 72333·
 2004 10 24295·
 2004 11 71271·
 2004 12 36281.
 2005 01  57287·
 2005 02  56293.
 2005 03  50330.
 2005 04  69348·
 2005 05  14390·
 2005 06  30331.
 2005 07  10326·
 2005 08  17344·
 2005 09  43294.
 2005 10  77350·
 2005 11  14308.
 2005 12  77324.
 2006 01 70349.
 2006 02 54341·
 2006 03 51399·
 2006 04 67360·
 2006 05 45400·
 2006 06 42343·
 2006 07 33318.
 2006 08 30299.
 2006 09 43323·
 2006 10 49395.
 2006 11 97377·
 2006 12 37383·
 2007 01  65370·
 2007 02  4337.
 2007 03  8343.
 2007 04  81363.
 2007 05  36373·
 2007 06  67327.
 2007 07  52345·
 2007 08  82395.
 2007 09  6421·
 2007 10  17400·
 2007 11  43370.
 2007 12  83356.
 2008 01 52348·
 2008 02 61361·
 2008 03 18363.
 2008 04 54382·
 2008 05 73368·
 2008 06 32328·
 2008 07 41307.
 2008 08 89324·
 2008 09 94377.
 2008 10 86357·
 2008 11 99366·
 2008 12 6403·
 2009 01  67419.
 2009 02  4435·
 2009 03  5429.
 2009 04  52432.
 2009 05  66417·
 2009 06  93373·
 2009 07  98318.
 2009 08  93303.
 2009 09  92333·
 2009 10  85299·
 2009 11  39383·
 2009 12  25472·
 2010 01 71509·
 2010 02 37497·
 2010 03 17470.
 2010 04 66391.
 2010 05 52344.
 2010 06 29366·
 2010 07 45284·
 2010 08 61286·
 2010 09 11348.
 2010 10 69359.
 2010 11 60426.
 2010 12 79445·
 2011 01  48462.
 2011 02  89427.
 2011 03  26396.
 2011 04  15367·
 2011 05  90326·
 2011 06  44313·
 2011 07  30296·
 2011 08  86330·
 2011 09  85356.
 2011 10  17396·
 2011 11  86402·
 2011 12  37428.
 2012 01 10468.
 2012 02 15481.
 2012 03 31420·
 2012 04 38459.
 2012 05 66451·
 2012 06 68435.
 2012 07 28375.
 2012 08 83436·
 2012 09 76410·
 2012 10 34445·
 2012 11 65457·
 2012 12 90510·
 2013 01  93494.
 2013 02  94463·
 2013 03  55458.
 2013 04  4432·
 2013 05  90529.
 2013 06  54463·
 2013 07  35503·
 2013 08  95492.
 2013 09  70510.
 2013 10  48484·
 2013 11  69436.
 2013 12  55501.
 2014 01 56487·
 2014 02 30483·
 2014 03 45518.
 2014 04 5489.
 2014 05 99497.
 2014 06 83452.
 2014 07 75481.
 2014 08 88472.
 2014 09 75476·
 2014 10 13462·
 2014 11 98447·
 2014 12 73460·
 2015 01  85465·
 2015 02  53535.
 2015 03  75555·
 2015 04  56537·
 2015 05  53564·
 2015 06  58522·
 2015 07  96469·
 2015 08  54471·
 2015 09  29469.
 2015 10  10511.
 2015 11  73533·
 2015 12  12463·
 2016 01 91461·
 2016 02 16495.
 2016 03 43501·
 2016 04 99484.
 2016 05 36593.
 2016 06 8496·
 2016 07 71470.
 2016 08 10464·
 2016 09 92498·
 2016 10 42499.
 2016 11 43517.
 2016 12 63554.
 2017 01  9535·
 2017 02  0544·
 2017 03  72556·
 2017 04  2525·
 2017 05  61523.
 2017 06  89485.


 2017 07  97491.
 2017 08  98498.
 2017 09  50534.
 2017 10  39570·
 2017 11  81586.
 2017 12  43605.
 2018 01 0622.
 2018 02 9622·
 2018 03 10569·
 2018 04 57594.
 2018 05 62561·
 2018 06 78510.
 2018 07 99484.
 2018 08 84461·
 2018 09 12504.
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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: Mexican, Education, Training, and Library Occupations: 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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