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 Series Title: Employment Level: Mexican, Building and Grounds Cleaning and Maintenance 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 91777·
 2000 02 85784·
 2000 03 69770.
 2000 04 33898·
 2000 05 91821.
 2000 06 59959·
 2000 07 57933.
 2000 08 32921·
 2000 09 13908·
 2000 10 88838.
 2000 11 2884.
 2000 12 86914.
 2001 01  9873·
 2001 02  53857.
 2001 03  16855.
 2001 04  39904·
 2001 05  52891·
 2001 06  61956·
 2001 07  39907·
 2001 08  60923·
 2001 09  45864·
 2001 10  44925·
 2001 11  33914·
 2001 12  43908·
 2002 01 12931.
 2002 02 58990·
 2002 03 86961.
 2002 04 81064·
 2002 05 31079·
 2002 06 85982·
 2002 07 10951·
 2002 08 99954.
 2002 09 94873.
 2002 10 32937.
 2002 11 431010.
 2002 12 84945.
 2003 01  86951·
 2003 02  29939.
 2003 03  49994.
 2003 04  591029·
 2003 05  31068.
 2003 06  351069·
 2003 07  151011·
 2003 08  411054·
 2003 09  97966.
 2003 10  30960·
 2003 11  551031·
 2003 12  761045.
 2004 01 42941·
 2004 02 21883·
 2004 03 5974·
 2004 04 311085.
 2004 05 381129·
 2004 06 401112·
 2004 07 301074·
 2004 08 31017·
 2004 09 121209·
 2004 10 441261.
 2004 11 161244·
 2004 12 91181·
 2005 01  141062.
 2005 02  131022.
 2005 03  771005.
 2005 04  931006.
 2005 05  191017·
 2005 06  55993.
 2005 07  511099.
 2005 08  261080·
 2005 09  271132·
 2005 10  21089.
 2005 11  0996·
 2005 12  01065.
 2006 01 641028·
 2006 02 91075·
 2006 03 121100.
 2006 04 361141·
 2006 05 811154·
 2006 06 591112.
 2006 07 11199·
 2006 08 771252·
 2006 09 511204·
 2006 10 591192·
 2006 11 41064.
 2006 12 931005·
 2007 01  771037.
 2007 02  391097.
 2007 03  841104.
 2007 04  771268·
 2007 05  841318·
 2007 06  561364·
 2007 07  291322·
 2007 08  481405·
 2007 09  211349·
 2007 10  931150.
 2007 11  521068·
 2007 12  521175·
 2008 01 641195·
 2008 02 561255·
 2008 03 911184·
 2008 04 571143.
 2008 05 141176·
 2008 06 761220·
 2008 07 91185·
 2008 08 561171·
 2008 09 961214.
 2008 10 101241·
 2008 11 921195·
 2008 12 711196·
 2009 01  601156·
 2009 02  401084·
 2009 03  561136·
 2009 04  431177·
 2009 05  821214·
 2009 06  731184·
 2009 07  361261.
 2009 08  431227·
 2009 09  621136·
 2009 10  391174·
 2009 11  971232.
 2009 12  651196.
 2010 01 261192·
 2010 02 961193.
 2010 03 261187·
 2010 04 281228·
 2010 05 231239·
 2010 06 251247·
 2010 07 361358·
 2010 08 751319·
 2010 09 301297.
 2010 10 341229·
 2010 11 651207.
 2010 12 771168·
 2011 01  471152.
 2011 02  521136.
 2011 03  761228.
 2011 04  271212.
 2011 05  981267.
 2011 06  381220·
 2011 07  561309·
 2011 08  441325·
 2011 09  351339.
 2011 10  731319·
 2011 11  191271.
 2011 12  731264·
 2012 01 331093.
 2012 02 641115·
 2012 03 21211·
 2012 04 831252.
 2012 05 921256.
 2012 06 411323·
 2012 07 681317·
 2012 08 681267·
 2012 09 381345·
 2012 10 621324.
 2012 11 61200.
 2012 12 461221·
 2013 01  211197·
 2013 02  91193·
 2013 03  281219.
 2013 04  631302.
 2013 05  171238.
 2013 06  881267.
 2013 07  721306.
 2013 08  871233.
 2013 09  251309.
 2013 10  311371.
 2013 11  11285.
 2013 12  121312·
 2014 01 711275.
 2014 02 931295·
 2014 03 21361.
 2014 04 581400·
 2014 05 61367·
 2014 06 581319·
 2014 07 901297.
 2014 08 681375.
 2014 09 51425·
 2014 10 321500·
 2014 11 01542.
 2014 12 131477.
 2015 01  691467·
 2015 02  451366.
 2015 03  981418·
 2015 04  851352·
 2015 05  221410·
 2015 06  561424·
 2015 07  691391·
 2015 08  41514·
 2015 09  151411.
 2015 10  451403.
 2015 11  281427·
 2015 12  151308·
 2016 01 241313·
 2016 02 201300·
 2016 03 121417.
 2016 04 861433·
 2016 05 491480·
 2016 06 111543.
 2016 07 841505·
 2016 08 111471·
 2016 09 151336·
 2016 10 751387·
 2016 11 321337·
 2016 12 111326.
 2017 01  731239·
 2017 02  951284·
 2017 03  691331.
 2017 04  281357·
 2017 05  981433.
 2017 06  771466·


 2017 07  321515.
 2017 08  311447·
 2017 09  901430·
 2017 10  521491.
 2017 11  851438.
 2017 12  161382.
 2018 01 761273·
 2018 02 761267·
 2018 03 161291·
 2018 04 21342·
 2018 05 41364.
 2018 06 331357.
 2018 07 371366·
 2018 08 311480·
 2018 09 521489.
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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, Building and Grounds Cleaning and Maintenance 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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