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 Series Title: Women, employed government wage and salary workers in Hospitals: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 33557·
 2012 03 2553.
 2012 02 67556·
 2012 01 86520·
 2011 12  43520.
 2011 11  22578.
 2011 10  12564.
 2011 09  28639.
 2011 08  70583.
 2011 07  91548·
 2011 06  8556.
 2011 05  19491·
 2011 04  63525.
 2011 03  90521.
 2011 02  68556.
 2011 01  3559.
 2010 12 99529·
 2010 11 26593.
 2010 10 29570·
 2010 09 49564·
 2010 08 77554.
 2010 07 30606·
 2010 06 55584·
 2010 05 51555.
 2010 04 23519·
 2010 03 60468·
 2010 02 34511·
 2010 01 28611·
 2009 12  87616.
 2009 11  96643.
 2009 10  78619·
 2009 09  24641.
 2009 08  45614.
 2009 07  45649.
 2009 06  25626·
 2009 05  9591.
 2009 04  97579.
 2009 03  39510·
 2009 02  38535·
 2009 01  77570.
 2008 12 69538·
 2008 11 35575·
 2008 10 5617·
 2008 09 46584·
 2008 08 10593.
 2008 07 14561·
 2008 06 39489·
 2008 05 61475·
 2008 04 96521·
 2008 03 83515.
 2008 02 79535.
 2008 01 92515·
 2007 12  29547·
 2007 11  73537.
 2007 10  85542.
 2007 09  31519·
 2007 08  32531·
 2007 07  41505·
 2007 06  48472.
 2007 05  99470.
 2007 04  57486.
 2007 03  70516.
 2007 02  78515·
 2007 01  39512·
 2006 12 78558·
 2006 11 65529.
 2006 10 16516·
 2006 09 22499.
 2006 08 97494.
 2006 07 57501.
 2006 06 22530·
 2006 05 39515.
 2006 04 38520·
 2006 03 5472·
 2006 02 86447.
 2006 01 12505.
 2005 12  52513·
 2005 11  89485·
 2005 10  20455·
 2005 09  84470·
 2005 08  15488·
 2005 07  16532.
 2005 06  61524·
 2005 05  24526·
 2005 04  26499.
 2005 03  17475·
 2005 02  74483.
 2005 01  26479·
 2004 12 12504·
 2004 11 50480·
 2004 10 45480·
 2004 09 10456·
 2004 08 22480·
 2004 07 96541·
 2004 06 88502·
 2004 05 19563.
 2004 04 32552·
 2004 03 61542.
 2004 02 40518.
 2004 01 23496.
 2003 12  42461.
 2003 11  78429.
 2003 10  65449.
 2003 09  16454·
 2003 08  78440·
 2003 07  2460.
 2003 06  50466·
 2003 05  18450.
 2003 04  90451·
 2003 03  16483.
 2003 02  8489.
 2003 01  71499·
 2002 12 54490·
 2002 11 26481.
 2002 10 77469·
 2002 09 45472·
 2002 08 70503·
 2002 07 64458.
 2002 06 20462·
 2002 05 35437.
 2002 04 62445·
 2002 03 86455·
 2002 02 25460.
 2002 01 60440.
 2001 12  83456.
 2001 11  74465·
 2001 10  5435·
 2001 09  64466·
 2001 08  6488·
 2001 07  35456·
 2001 06  97456·
 2001 05  15414.
 2001 04  33442·
 2001 03  0478·
 2001 02  65487.
 2001 01  8464.
 2000 12 89473·
 2000 11 26425.
 2000 10 97472·
 2000 09 63487.
 2000 08 24485·
 2000 07 95493·
 2000 06 4498.
 2000 05 22494·
 2000 04 14521·
 2000 03 13517·
 2000 02 26521·
 2000 01 57431·
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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: Women, employed government wage and salary workers in Hospitals: 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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