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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations in Nondurable Goods Manufacturing Industry: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 9158·
 2012 03 5059·
 2012 02 5965.
 2012 01 2058·
 2011 12  6049·
 2011 11  954.
 2011 10  9745·
 2011 09  8553.
 2011 08  1435.
 2011 07  8548.
 2011 06  5454·
 2011 05  6730.
 2011 04  428·
 2011 03  5936·
 2011 02  4465.
 2011 01  1154.
 2010 12 465.
 2010 11 4063.
 2010 10 563.
 2010 09 8553.
 2010 08 1540.
 2010 07 5749·
 2010 06 9963.
 2010 05 8565.
 2010 04 6461·
 2010 03 6848.
 2010 02 1445.
 2010 01 2832.
 2009 12  9943.
 2009 11  5549.
 2009 10  6343·
 2009 09  5940.
 2009 08  9732·
 2009 07  2330.
 2009 06  8424.
 2009 05  4823.
 2009 04  5741.
 2009 03  639.
 2009 02  4140·
 2009 01  8847.
 2008 12 634.
 2008 11 5853.
 2008 10 2045.
 2008 09 9950·
 2008 08 9347.
 2008 07 6328·
 2008 06 3436.
 2008 05 2441.
 2008 04 9544.
 2008 03 2636.
 2008 02 2235.
 2008 01 3343·
 2007 12  1044·
 2007 11  8044.
 2007 10  4765·
 2007 09  2162.
 2007 08  6668·
 2007 07  8063.
 2007 06  9642·
 2007 05  549.
 2007 04  1152·
 2007 03  947.
 2007 02  8263·
 2007 01  3046.
 2006 12 2334.
 2006 11 7445·
 2006 10 4348.
 2006 09 6647·
 2006 08 046·
 2006 07 543·
 2006 06 4330·
 2006 05 634·
 2006 04 6834·
 2006 03 5946·
 2006 02 6859·
 2006 01 7060.
 2005 12  7968.
 2005 11  1970.
 2005 10  3255.
 2005 09  256.
 2005 08  635·
 2005 07  9042·
 2005 06  7349.
 2005 05  7166·
 2005 04  5143·
 2005 03  534·
 2005 02  5331.
 2005 01  7127.
 2004 12 3947·
 2004 11 2052.
 2004 10 6144·
 2004 09 2145.
 2004 08 2048·
 2004 07 1641.
 2004 06 943.
 2004 05 6648·
 2004 04 6938·
 2004 03 139·
 2004 02 3641.
 2004 01 7353.
 2003 12  8853·
 2003 11  557.
 2003 10  361·
 2003 09  3958.
 2003 08  250·
 2003 07  8735·
 2003 06  049·
 2003 05  8155·
 2003 04  6051·
 2003 03  2672.
 2003 02  3866.
 2003 01  4550·
 2002 12 3848.
 2002 11 3128·
 2002 10 5719.
 2002 09 9833.
 2002 08 3746·
 2002 07 3246·
 2002 06 1863.
 2002 05 3648·
 2002 04 8247.
 2002 03 8645.
 2002 02 950.
 2002 01 7758·
 2001 12  2464.
 2001 11  7558.
 2001 10  4551.
 2001 09  6546·
 2001 08  3758·
 2001 07  547.
 2001 06  6150·
 2001 05  705·
 2001 04  227·
 2001 03  89.
 2001 02  22
 2001 01  869.
 2000 12 513·
 2000 11 4110.
 2000 10 152.
 2000 08 323.
 2000 07 364.
 2000 06 868·
 2000 05 5310.
 2000 04 5213·
 2000 03 917.
 2000 02 4813.
 2000 01 7442·
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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: Employment Level: Farming, Fishing, and Forestry Occupations in Nondurable Goods Manufacturing Industry: 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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