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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 38307·
 2000 02 66288·
 2000 03 23305.
 2000 04 60262·
 2000 05 54283.
 2000 06 85271.
 2000 07 33248.
 2000 08 10271·
 2000 09 6286·
 2000 10 71246·
 2000 11 14247·
 2000 12 27271.
 2001 01  43298·
 2001 02  6306·
 2001 03  76339.
 2001 04  56331.
 2001 05  41316.
 2001 06  96309·
 2001 07  60309.
 2001 08  66295·
 2001 09  0316.
 2001 10  74278.
 2001 11  26230·
 2001 12  50276.
 2002 01 46269.
 2002 02 95300.
 2002 03 64307.
 2002 04 29274·
 2002 05 29276.
 2002 06 42274·
 2002 07 86277.
 2002 08 46322.
 2002 09 24349·
 2002 10 21356·
 2002 11 30342.
 2002 12 69329.
 2003 01  33347·
 2003 02  63291.
 2003 03  59279.
 2003 04  95298·
 2003 05  79306·
 2003 06  26301·
 2003 07  60250.
 2003 08  41316.
 2003 09  14304.
 2003 10  91335·
 2003 11  47336.
 2003 12  51312·
 2004 01 13275.
 2004 02 64264·
 2004 03 58291.
 2004 04 95351.
 2004 05 76403.
 2004 06 78356.
 2004 07 56341·
 2004 08 68295.
 2004 09 30333.
 2004 10 89295.
 2004 11 27271·
 2004 12 87281.
 2005 01  23287.
 2005 02  78293.
 2005 03  86330·
 2005 04  98348.
 2005 05  32390·
 2005 06  52331·
 2005 07  70326.
 2005 08  69344·
 2005 09  57294.
 2005 10  44350·
 2005 11  42308·
 2005 12  94324.
 2006 01 23349·
 2006 02 8341·
 2006 03 90399·
 2006 04 93360·
 2006 05 81400.
 2006 06 28343·
 2006 07 27318.
 2006 08 10299.
 2006 09 6323.
 2006 10 9395.
 2006 11 90377·
 2006 12 14383.
 2007 01  98370·
 2007 02  84337.
 2007 03  43343.
 2007 04  99363.
 2007 05  84373·
 2007 06  9327.
 2007 07  74345·
 2007 08  85395.
 2007 09  12421.
 2007 10  66400.
 2007 11  94370.
 2007 12  14356·
 2008 01 60348·
 2008 02 61361·
 2008 03 43363·
 2008 04 57382·
 2008 05 26368·
 2008 06 26328.
 2008 07 84307·
 2008 08 8324·
 2008 09 37377·
 2008 10 17357.
 2008 11 3366·
 2008 12 86403.
 2009 01  43419·
 2009 02  17435.
 2009 03  14429.
 2009 04  34432·
 2009 05  19417.
 2009 06  31373·
 2009 07  55318.
 2009 08  23303.
 2009 09  66333·
 2009 10  92299.
 2009 11  89383.
 2009 12  45472.
 2010 01 8509·
 2010 02 57497.
 2010 03 3470.
 2010 04 22391·
 2010 05 97344.
 2010 06 6366·
 2010 07 11284.
 2010 08 95286.
 2010 09 8348·
 2010 10 46359.
 2010 11 50426.
 2010 12 35445.
 2011 01  42462·
 2011 02  10427.
 2011 03  84396·
 2011 04  36367·
 2011 05  22326·
 2011 06  53313·
 2011 07  99296·
 2011 08  17330·
 2011 09  1356·
 2011 10  58396·
 2011 11  10402.
 2011 12  22428·
 2012 01 53468.
 2012 02 30481·
 2012 03 53420.
 2012 04 20459·
 2012 05 79451.
 2012 06 2435·
 2012 07 93375.
 2012 08 6436·
 2012 09 4410.
 2012 10 31445.
 2012 11 16457·
 2012 12 98510·
 2013 01  78494·
 2013 02  97463·
 2013 03  36458·
 2013 04  41432·
 2013 05  78529.
 2013 06  8463.
 2013 07  90503·
 2013 08  3492·
 2013 09  3510·
 2013 10  96484·
 2013 11  42436·
 2013 12  79501.
 2014 01 78487·
 2014 02 16483·
 2014 03 79518.
 2014 04 88489·
 2014 05 55497·
 2014 06 50452.
 2014 07 14481.
 2014 08 75472·
 2014 09 8476·
 2014 10 6462·
 2014 11 85447.
 2014 12 8460·
 2015 01  38465.
 2015 02  14535.
 2015 03  55555.
 2015 04  81537·
 2015 05  70564·
 2015 06  32522.
 2015 07  12469.
 2015 08  14471.
 2015 09  55469·
 2015 10  41511.
 2015 11  69533·
 2015 12  50463·
 2016 01 68461.
 2016 02 48495.
 2016 03 63501·
 2016 04 60484.
 2016 05 9593·
 2016 06 84496.
 2016 07 58470·
 2016 08 36464·
 2016 09 5498.
 2016 10 6499.
 2016 11 41517·
 2016 12 99554.
 2017 01  4535.
 2017 02  95544.
 2017 03  26556.
 2017 04  92525.
 2017 05  83523.
 2017 06  59485.
 2017 07  49491.
 2017 08  84498·


 2017 09  42534·
 2017 10  28570·
 2017 11  75586.
 2017 12  70605.
 2018 01 7622.
 2018 02 61622·
 2018 03 91569·
 2018 04 69594.
 2018 05 27561.
 2018 06 37510·
 2018 07 10484·
 2018 08 25461.
 2018 09 79504.
 2018 10 64548.
 2018 11 69573·
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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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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