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 Series Title: Population Level: 25-34 years, Hispanic or Latino Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 524080.
 2012 03 894077.
 2012 02 94075.
 2012 01 764072.
 2011 12  793747·
 2011 11  103743.
 2011 10  623739·
 2011 09  593736·
 2011 08  43732·
 2011 07  603729·
 2011 06  473725·
 2011 05  723721·
 2011 04  783718·
 2011 03  223715·
 2011 02  783712·
 2011 01  593709.
 2010 12 743727.
 2010 11 23722.
 2010 10 913718·
 2010 09 893714·
 2010 08 953709·
 2010 07 313705.
 2010 06 503701·
 2010 05 573696.
 2010 04 643693·
 2010 03 663689·
 2010 02 423685.
 2010 01 813681.
 2009 12  333711.
 2009 11  903708·
 2009 10  823704.
 2009 09  53701.
 2009 08  773698·
 2009 07  83695.
 2009 06  53692·
 2009 05  03690·
 2009 04  973687·
 2009 03  523684.
 2009 02  773681.
 2009 01  583678·
 2008 12 173738·
 2008 11 793733.
 2008 10 833728·
 2008 09 993723·
 2008 08 883717·
 2008 07 713711.
 2008 06 383706·
 2008 05 683701·
 2008 04 853697·
 2008 03 343691·
 2008 02 783687·
 2008 01 333681·
 2007 12  103732.
 2007 11  993726.
 2007 10  683720.
 2007 09  883714.
 2007 08  873707·
 2007 07  243701.
 2007 06  953695.
 2007 05  533689·
 2007 04  663683.
 2007 03  903677.
 2007 02  713671.
 2007 01  713665·
 2006 12 243625·
 2006 11 43618.
 2006 10 353612.
 2006 09 133605.
 2006 08 603598.
 2006 07 973591·
 2006 06 493586.
 2006 05 713580·
 2006 04 993574·
 2006 03 253569.
 2006 02 23563.
 2006 01 663558·
 2005 12  933572·
 2005 11  723564·
 2005 10  63557.
 2005 09  413549.
 2005 08  173540·
 2005 07  433532·
 2005 06  993524·
 2005 05  663517.
 2005 04  713509·
 2005 03  693501.
 2005 02  453494.
 2005 01  343486·
 2004 12 803490.
 2004 11 93483·
 2004 10 303475·
 2004 09 643467.
 2004 08 953459.
 2004 07 423451·
 2004 06 683443.
 2004 05 23435·
 2004 04 913427.
 2004 03 763418·
 2004 02 973410.
 2004 01 163402·
 2003 12  683533·
 2003 11  433522.
 2003 10  803512·
 2003 09  993500.
 2003 08  533489·
 2003 07  983478·
 2003 06  43467·
 2003 05  723455·
 2003 04  953444.
 2003 03  253434·
 2003 02  823423.
 2003 01  793413·
 2002 12 693356.
 2002 11 293331.
 2002 10 533305·
 2002 09 883221.
 2002 08 773225·
 2002 07 423249·
 2002 06 793303·
 2002 05 943342.
 2002 04 443307·
 2002 03 203278.
 2002 02 493303.
 2002 01 153176·
 2001 12  193220·
 2001 11  463271.
 2001 10  743194.
 2001 09  973192·
 2001 08  783170.
 2001 07  263140·
 2001 06  933185·
 2001 05  83216.
 2001 04  233234.
 2001 03  913117·
 2001 02  693229·
 2001 01  423205.
 2000 12 773144.
 2000 11 983097·
 2000 10 893096.
 2000 09 183088.
 2000 08 923069.
 2000 07 303060·
 2000 06 673009·
 2000 05 813069·
 2000 04 433095.
 2000 03 923109.
 2000 02 413095.
 2000 01 03095·
 1999 12  292878·
 1999 11  162779·
 1999 10  722711·
 1999 09  682765·
 1999 08  782635.
 1999 07  582611·
 1999 06  502605.
 1999 05  62688·
 1999 04  392741·
 1999 03  22725.
 1999 02  882743.
 1999 01  572608.
 1998 12 872604·
 1998 11 522596.
 1998 10 222509·
 1998 09 892550·
 1998 08 232474.
 1998 07 412433·
 1998 06 162456.
 1998 05 992534·
 1998 04 722556·
 1998 03 252591·
 1998 02 582629·
 1998 01 32539·
 1997 12  852480·
 1997 11  872519·
 1997 10  602507·
 1997 09  482573.
 1997 08  362505.
 1997 07  312522·
 1997 06  612540.
 1997 05  12560·
 1997 04  272540·
 1997 03  922579.
 1997 02  242576.
 1997 01  582501·
 1996 12 832505.
 1996 11 242477·
 1996 10 362425.
 1996 09 362522.
 1996 08 542515·
 1996 07 92523·
 1996 06 102538.
 1996 05 802520.
 1996 04 162514.
 1996 03 552453·
 1996 02 842446·
 1996 01 602428.
 1995 12  692458.
 1995 11  932395·
 1995 10  212401.
 1995 09  702391.
 1995 08  372343.
 1995 07  792322·
 1995 06  92369·
 1995 05  282348.
 1995 04  732429.
 1995 03  952414·
 1995 02  612438.
 1995 01  792409.
 1994 12 512417·
 1994 11 482377.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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: Population Level: 25-34 years, Hispanic or Latino Women: 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

Make charts for Okun's Law and Phillip's Curve

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