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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 78777·
 2000 02 27784.
 2000 03 59770·
 2000 04 69898.
 2000 05 78821·
 2000 06 9959.
 2000 07 87933·
 2000 08 66921.
 2000 09 82908·
 2000 10 27838·
 2000 11 54884.
 2000 12 0914.
 2001 01  40873.
 2001 02  63857.
 2001 03  72855·
 2001 04  14904.
 2001 05  28891·
 2001 06  23956·
 2001 07  80907·
 2001 08  78923.
 2001 09  46864.
 2001 10  38925·
 2001 11  39914.
 2001 12  85908·
 2002 01 19931.
 2002 02 67990.
 2002 03 38961·
 2002 04 551064·
 2002 05 981079·
 2002 06 89982·
 2002 07 91951·
 2002 08 31954.
 2002 09 58873·
 2002 10 12937.
 2002 11 341010.
 2002 12 84945.
 2003 01  99951.
 2003 02  68939·
 2003 03  30994·
 2003 04  71029·
 2003 05  481068·
 2003 06  131069·
 2003 07  691011·
 2003 08  191054·
 2003 09  54966·
 2003 10  28960.
 2003 11  611031·
 2003 12  641045.
 2004 01 93941·
 2004 02 21883·
 2004 03 46974·
 2004 04 131085·
 2004 05 651129·
 2004 06 231112·
 2004 07 861074.
 2004 08 571017·
 2004 09 951209.
 2004 10 911261.
 2004 11 701244·
 2004 12 181181·
 2005 01  341062·
 2005 02  51022·
 2005 03  91005.
 2005 04  391006.
 2005 05  581017·
 2005 06  74993.
 2005 07  421099.
 2005 08  891080·
 2005 09  661132.
 2005 10  291089·
 2005 11  32996.
 2005 12  621065.
 2006 01 851028·
 2006 02 251075.
 2006 03 661100·
 2006 04 771141·
 2006 05 641154.
 2006 06 461112·
 2006 07 581199.
 2006 08 791252·
 2006 09 781204·
 2006 10 971192.
 2006 11 461064·
 2006 12 371005.
 2007 01  291037·
 2007 02  101097.
 2007 03  921104.
 2007 04  451268.
 2007 05  421318·
 2007 06  421364.
 2007 07  841322·
 2007 08  211405.
 2007 09  671349.
 2007 10  741150.
 2007 11  351068·
 2007 12  111175·
 2008 01 791195.
 2008 02 131255.
 2008 03 831184.
 2008 04 831143·
 2008 05 791176·
 2008 06 911220·
 2008 07 911185·
 2008 08 311171·
 2008 09 921214·
 2008 10 651241·
 2008 11 471195·
 2008 12 751196.
 2009 01  691156.
 2009 02  151084·
 2009 03  641136·
 2009 04  581177.
 2009 05  851214.
 2009 06  491184.
 2009 07  791261.
 2009 08  511227·
 2009 09  401136.
 2009 10  981174·
 2009 11  561232.
 2009 12  461196.
 2010 01 601192·
 2010 02 191193.
 2010 03 821187.
 2010 04 641228.
 2010 05 951239.
 2010 06 941247·
 2010 07 701358.
 2010 08 471319·
 2010 09 211297.
 2010 10 291229.
 2010 11 581207.
 2010 12 661168.
 2011 01  371152·
 2011 02  561136·
 2011 03  91228.
 2011 04  151212·
 2011 05  701267·
 2011 06  311220·
 2011 07  121309.
 2011 08  121325·
 2011 09  701339.
 2011 10  361319·
 2011 11  781271·
 2011 12  21264.
 2012 01 121093.
 2012 02 781115·
 2012 03 451211·
 2012 04 541252.
 2012 05 961256·
 2012 06 891323·
 2012 07 781317·
 2012 08 621267·
 2012 09 481345.
 2012 10 241324·
 2012 11 621200.
 2012 12 451221.
 2013 01  191197.
 2013 02  661193.
 2013 03  121219·
 2013 04  481302·
 2013 05  831238·
 2013 06  221267.
 2013 07  661306·
 2013 08  391233.
 2013 09  411309.
 2013 10  221371.
 2013 11  851285.
 2013 12  131312.
 2014 01 191275.
 2014 02 241295.
 2014 03 591361·
 2014 04 891400.
 2014 05 671367·
 2014 06 91319·
 2014 07 991297.
 2014 08 101375.
 2014 09 591425·
 2014 10 851500.
 2014 11 451542·
 2014 12 471477·
 2015 01  981467·
 2015 02  811366.
 2015 03  581418·
 2015 04  931352.
 2015 05  71410·
 2015 06  561424.
 2015 07  261391.
 2015 08  671514.
 2015 09  381411·
 2015 10  911403.
 2015 11  631427.
 2015 12  131308.
 2016 01 661313·
 2016 02 921300.
 2016 03 71417·
 2016 04 21433·
 2016 05 911480·
 2016 06 911543·
 2016 07 201505·
 2016 08 261471·
 2016 09 391336.
 2016 10 441387.
 2016 11 891337·
 2016 12 51326.
 2017 01  591239·
 2017 02  351284·
 2017 03  291331.
 2017 04  831357.
 2017 05  281433·
 2017 06  681466·
 2017 07  771515·
 2017 08  291447.
 2017 09  461430·
 2017 10  761491·
 2017 11  961438.


 2017 12  381382·
 2018 01 371273·
 2018 02 151267.
 2018 03 731291.
 2018 04 281342·
 2018 05 541364·
 2018 06 671357.
 2018 07 221366·
 2018 08 431480·
 2018 09 701489.
 2018 10 381617.
 2018 11 811552.
 2018 12 541589.
 2019 01  861353·
 2019 02  611368.
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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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