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 Series Title: Women, employed government wage and salary workers in Real estate and rental and leasing: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 6857·
 2012 03 7976·
 2012 02 3773.
 2012 01 2752·
 2011 12  5545·
 2011 11  3332.
 2011 10  7238·
 2011 09  1553.
 2011 08  8446.
 2011 07  6050.
 2011 06  8259·
 2011 05  7669·
 2011 04  458.
 2011 03  4249.
 2011 02  8270.
 2011 01  5654.
 2010 12 9252·
 2010 11 8667.
 2010 10 740·
 2010 09 2265·
 2010 08 4754.
 2010 07 2451.
 2010 06 2351·
 2010 05 7034·
 2010 04 9528·
 2010 03 1127.
 2010 02 1631.
 2010 01 1836·
 2009 12  8627.
 2009 11  3037.
 2009 10  9935·
 2009 09  1037·
 2009 08  9647.
 2009 07  8843·
 2009 06  1161.
 2009 05  1566.
 2009 04  2548·
 2009 03  1528·
 2009 02  1416.
 2009 01  2927·
 2008 12 9835.
 2008 11 6936·
 2008 10 9538·
 2008 09 6936·
 2008 08 6739.
 2008 07 3135·
 2008 06 6941.
 2008 05 8045·
 2008 04 549.
 2008 03 847.
 2008 02 7337·
 2008 01 3138.
 2007 12  1451.
 2007 11  3259.
 2007 10  6965.
 2007 09  1652.
 2007 08  1948·
 2007 07  5838.
 2007 06  4643·
 2007 05  5556.
 2007 04  7150.
 2007 03  7054·
 2007 02  1642·
 2007 01  9149.
 2006 12 4554.
 2006 11 7339.
 2006 10 1740·
 2006 09 9336·
 2006 08 4042.
 2006 07 9939·
 2006 06 1328·
 2006 05 5736·
 2006 04 8326.
 2006 03 550.
 2006 02 9246·
 2006 01 033·
 2005 12  2542.
 2005 11  7236.
 2005 10  6520.
 2005 09  6840·
 2005 08  3920.
 2005 07  727·
 2005 06  7134.
 2005 05  2853.
 2005 04  2760.
 2005 03  4256·
 2005 02  7348·
 2005 01  7637.
 2004 12 1538.
 2004 11 3334.
 2004 10 5836.
 2004 09 3134.
 2004 08 5233.
 2004 07 6225·
 2004 06 4135.
 2004 05 3632.
 2004 04 1453·
 2004 03 3547.
 2004 02 5750.
 2004 01 6153·
 2003 12  142.
 2003 11  8535.
 2003 10  7128·
 2003 09  031.
 2003 08  3936.
 2003 07  6849.
 2003 06  7154.
 2003 05  7148·
 2003 04  7847.
 2003 03  6547·
 2003 02  6941.
 2003 01  2049·
 2002 12 9454·
 2002 11 8345·
 2002 10 246.
 2002 09 1630.
 2002 08 8635·
 2002 07 5433·
 2002 06 3547·
 2002 05 5156.
 2002 04 8163·
 2002 03 3487.
 2002 02 5481·
 2002 01 4755·
 2001 12  2944.
 2001 11  534.
 2001 10  7441.
 2001 09  4656.
 2001 08  441·
 2001 07  7550·
 2001 06  3050.
 2001 05  1857.
 2001 04  853.
 2001 03  7348·
 2001 02  8840·
 2001 01  5745·
 2000 12 6657·
 2000 11 5757·
 2000 10 3450·
 2000 09 8252.
 2000 08 2862·
 2000 07 951·
 2000 06 8153.
 2000 05 3845.
 2000 04 6957·
 2000 03 3661·
 2000 02 6755·
 2000 01 9252.
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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 Real estate and rental and leasing: 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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