Overview

The Current Population Survey (CPS) is a monthly survey of households conducted by the Bureau of Census for the Bureau of Labor Statistics. It provides a comprehensive body of data on the labor force, employment, unemployment, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics.

http://www.bls.gov/cps/home.htm

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Field Descriptions

JSON Path Type Comment Example Value
[0].data.Civilian labor force.Black or African American.All.units unicode Number in thousands
[0].data.Civilian labor force.Black or African American.All.value float 8334.0
[0].data.Unemployment rate.White.All.units unicode Percent or rate
[0].data.Unemployment rate.White.All.value float 5.9
[0].data.Employment-population ratio.White dict {u'All': {u'units': u'Percent or rate', u'value': 56.1}, u'Men': {u'units': u'Percent or rate', u'value': 77.7}, u'Women': {u'units': u'Percent or rate', u'value': 40.5}}
[0].data.Employment-population ratio.Black or African American dict {u'All': {u'units': u'Percent or rate', u'value': 51.4}, u'Men': {u'units': u'Percent or rate', u'value': 69.3}, u'Women': {u'units': u'Percent or rate', u'value': 45.9}}
[0].data.Employment-population ratio.Asian dict {u'All': 0}
[0].data.Civilian labor force.White.All dict {u'units': u'Number in thousands', u'value': 75608.0}
[0].data.Civilian labor force.White.Men dict {u'units': u'Number in thousands', u'value': 43514.0}
[0].data.Civilian labor force.White.Women dict {u'units': u'Number in thousands', u'value': 25728.0}
[0].data.Unemployment rate.White.All dict {u'units': u'Percent or rate', u'value': 5.9}
[0].data.Unemployment rate.White.Men dict {u'units': u'Percent or rate', u'value': 4.8}
[0].data.Unemployment rate.White.Women dict {u'units': u'Percent or rate', u'value': 5.1}
[0].data.Unemployed.Black or African American.Men.units unicode Number in thousands
[0].data.Unemployed.Black or African American.Men.value float 378.0
[0].data.Unemployment rate.Black or African American.All.units unicode Percent or rate
[0].data.Unemployment rate.Black or African American.All.value float 11.6
[0].data.Civilian noninstitutional population.White dict {u'All': {u'units': u'Number in thousands', u'value': 126749.0}}
[0].data.Civilian noninstitutional population.Black or African American dict {u'All': {u'units': u'Number in thousands', u'value': 14332.0}}
[0].data.Civilian noninstitutional population.Asian dict {u'All': 0}
[0].data.Civilian labor force participation rate.White dict {u'All': {u'units': u'Percent or rate', u'value': 59.7}, u'Men': {u'units': u'Percent or rate', u'value': 81.7}, u'Women': {u'units': u'Percent or rate', u'value': 42.7}}
[0].data.Civilian labor force participation rate.Black or African American dict {u'All': {u'units': u'Percent or rate', u'value': 58.1}, u'Men': {u'units': u'Percent or rate', u'value': 76.2}, u'Women': {u'units': u'Percent or rate', u'value': 50.9}}
[0].data.Civilian labor force participation rate.Asian dict {u'All': 0}
[0].data.Employed.Black or African American.Women.units unicode Number in thousands
[0].data.Employed.Black or African American.Women.value float 3156.0
[0].data.Unemployed.White.Men.units unicode Number in thousands
[0].data.Unemployed.White.Men.value float 2096.0
[0].data.Civilian labor force participation rate.Asian.All int 0
[0].data.Employment-population ratio.Black or African American.All.units unicode Percent or rate
[0].data.Employment-population ratio.Black or African American.All.value float 51.4
[0].data.Unemployed.White.Women.units unicode Number in thousands
[0].data.Unemployed.White.Women.value float 1325.0
[0].data.Civilian labor force participation rate.Black or African American.Women.units unicode Percent or rate
[0].data.Civilian labor force participation rate.Black or African American.Women.value float 50.9
[0].data.Unemployment rate.White.Women.units unicode Percent or rate
[0].data.Unemployment rate.White.Women.value float 5.1
[0].data.Employment-population ratio.Black or African American.All dict {u'units': u'Percent or rate', u'value': 51.4}
[0].data.Employment-population ratio.Black or African American.Men dict {u'units': u'Percent or rate', u'value': 69.3}
[0].data.Employment-population ratio.Black or African American.Women dict {u'units': u'Percent or rate', u'value': 45.9}
[0].data.Unemployed.Black or African American.All.units unicode Number in thousands
[0].data.Unemployed.Black or African American.All.value float 967.0
[0].data.Unemployment rate.White dict {u'All': {u'units': u'Percent or rate', u'value': 5.9}, u'Men': {u'units': u'Percent or rate', u'value': 4.8}, u'Women': {u'units': u'Percent or rate', u'value': 5.1}}
[0].data.Unemployment rate.Black or African American dict {u'All': {u'units': u'Percent or rate', u'value': 11.6}, u'Men': {u'units': u'Percent or rate', u'value': 9.0}, u'Women': {u'units': u'Percent or rate', u'value': 9.8}}
[0].data.Unemployment rate.Asian dict {u'All': 0}
[0].data.Unemployment rate.Black or African American.All dict {u'units': u'Percent or rate', u'value': 11.6}
[0].data.Unemployment rate.Black or African American.Men dict {u'units': u'Percent or rate', u'value': 9.0}
[0].data.Unemployment rate.Black or African American.Women dict {u'units': u'Percent or rate', u'value': 9.8}
[0].data.Civilian noninstitutional population.White.All dict {u'units': u'Number in thousands', u'value': 126749.0}
[0].data.Civilian labor force.White.Men.units unicode Number in thousands
[0].data.Civilian labor force.White.Men.value float 43514.0
[0].year int 1972
[0].data dict {u'Civilian labor force': {u'White': {u'All': {u'units': u'Number in thousands', u'value': 75608.0}, u'Men': {u'units': u'Number in thousands', u'value': 43514.0}, u'Women': {u'units': u'Number in thousands', u'value': 25728.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 8334.0}, u'Men': {u'units': u'Number in thousands', u'value': 4180.0}, u'Women': {u'units': u'Number in thousands', u'value': 3498.0}}, u'Asian': {u'All': 0}}, u'Not in labor force': {u'White': {u'All': 0}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 5998.0}}, u'Asian': {u'All': 0}}, u'Unemployed': {u'White': {u'All': {u'units': u'Number in thousands', u'value': 4439.0}, u'Men': {u'units': u'Number in thousands', u'value': 2096.0}, u'Women': {u'units': u'Number in thousands', u'value': 1325.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 967.0}, u'Men': {u'units': u'Number in thousands', u'value': 378.0}, u'Women': {u'units': u'Number in thousands', u'value': 343.0}}, u'Asian': {u'All': 0}}, u'Civilian labor force participation rate': {u'White': {u'All': {u'units': u'Percent or rate', u'value': 59.7}, u'Men': {u'units': u'Percent or rate', u'value': 81.7}, u'Women': {u'units': u'Percent or rate', u'value': 42.7}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 58.1}, u'Men': {u'units': u'Percent or rate', u'value': 76.2}, u'Women': {u'units': u'Percent or rate', u'value': 50.9}}, u'Asian': {u'All': 0}}, u'Unemployment rate': {u'White': {u'All': {u'units': u'Percent or rate', u'value': 5.9}, u'Men': {u'units': u'Percent or rate', u'value': 4.8}, u'Women': {u'units': u'Percent or rate', u'value': 5.1}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 11.6}, u'Men': {u'units': u'Percent or rate', u'value': 9.0}, u'Women': {u'units': u'Percent or rate', u'value': 9.8}}, u'Asian': {u'All': 0}}, u'Civilian noninstitutional population': {u'White': {u'All': {u'units': u'Number in thousands', u'value': 126749.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 14332.0}}, u'Asian': {u'All': 0}}, u'Employed': {u'White': {u'All': {u'units': u'Number in thousands', u'value': 71169.0}, u'Men': {u'units': u'Number in thousands', u'value': 41418.0}, u'Women': {u'units': u'Number in thousands', u'value': 24403.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 7367.0}, u'Men': {u'units': u'Number in thousands', u'value': 3802.0}, u'Women': {u'units': u'Number in thousands', u'value': 3156.0}}, u'Asian': {u'All': 0}}, u'Employment-population ratio': {u'White': {u'All': {u'units': u'Percent or rate', u'value': 56.1}, u'Men': {u'units': u'Percent or rate', u'value': 77.7}, u'Women': {u'units': u'Percent or rate', u'value': 40.5}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 51.4}, u'Men': {u'units': u'Percent or rate', u'value': 69.3}, u'Women': {u'units': u'Percent or rate', u'value': 45.9}}, u'Asian': {u'All': 0}}}
[0].month int 1
[0].data.Not in labor force.White dict {u'All': 0}
[0].data.Not in labor force.Black or African American dict {u'All': {u'units': u'Number in thousands', u'value': 5998.0}}
[0].data.Not in labor force.Asian dict {u'All': 0}
[0].data.Employed.White.Women.units unicode Number in thousands
[0].data.Employed.White.Women.value float 24403.0
[0].data.Civilian labor force participation rate.Black or African American.Men.units unicode Percent or rate
[0].data.Civilian labor force participation rate.Black or African American.Men.value float 76.2
[0].data.Civilian noninstitutional population.Black or African American.All.units unicode Number in thousands
[0].data.Civilian noninstitutional population.Black or African American.All.value float 14332.0
[0].data.Employed.White dict {u'All': {u'units': u'Number in thousands', u'value': 71169.0}, u'Men': {u'units': u'Number in thousands', u'value': 41418.0}, u'Women': {u'units': u'Number in thousands', u'value': 24403.0}}
[0].data.Employed.Black or African American dict {u'All': {u'units': u'Number in thousands', u'value': 7367.0}, u'Men': {u'units': u'Number in thousands', u'value': 3802.0}, u'Women': {u'units': u'Number in thousands', u'value': 3156.0}}
[0].data.Employed.Asian dict {u'All': 0}
[0].data.Unemployment rate.White.Men.units unicode Percent or rate
[0].data.Unemployment rate.White.Men.value float 4.8
[0].data.Unemployment rate.Asian.All int 0
[0].data.Civilian noninstitutional population.Asian.All int 0
[0].data.Civilian labor force.Asian.All int 0
[0].data.Employment-population ratio.Asian.All int 0
[0].data.Employed.Black or African American.Men.units unicode Number in thousands
[0].data.Employed.Black or African American.Men.value float 3802.0
[0].data.Civilian noninstitutional population.White.All.units unicode Number in thousands
[0].data.Civilian noninstitutional population.White.All.value float 126749.0
[0].data.Civilian labor force participation rate.White.All.units unicode Percent or rate
[0].data.Civilian labor force participation rate.White.All.value float 59.7
[0].data.Unemployment rate.Black or African American.Men.units unicode Percent or rate
[0].data.Unemployment rate.Black or African American.Men.value float 9.0
[0].data.Unemployed.Black or African American.All dict {u'units': u'Number in thousands', u'value': 967.0}
[0].data.Unemployed.Black or African American.Men dict {u'units': u'Number in thousands', u'value': 378.0}
[0].data.Unemployed.Black or African American.Women dict {u'units': u'Number in thousands', u'value': 343.0}
[0].data.Employment-population ratio.Black or African American.Women.units unicode Percent or rate
[0].data.Employment-population ratio.Black or African American.Women.value float 45.9
[0].data.Employment-population ratio.White.All.units unicode Percent or rate
[0].data.Employment-population ratio.White.All.value float 56.1
[0].data.Unemployed.White.All dict {u'units': u'Number in thousands', u'value': 4439.0}
[0].data.Unemployed.White.Men dict {u'units': u'Number in thousands', u'value': 2096.0}
[0].data.Unemployed.White.Women dict {u'units': u'Number in thousands', u'value': 1325.0}
[0].data.Employed.Black or African American.All.units unicode Number in thousands
[0].data.Employed.Black or African American.All.value float 7367.0
[0].data.Unemployed.Black or African American.Women.units unicode Number in thousands
[0].data.Unemployed.Black or African American.Women.value float 343.0
[0].data.Civilian labor force.White.All.units unicode Number in thousands
[0].data.Civilian labor force.White.All.value float 75608.0
[0].data.Civilian labor force participation rate.White.Women.units unicode Percent or rate
[0].data.Civilian labor force participation rate.White.Women.value float 42.7
[0].data.Unemployed.Asian.All int 0
[0].data.Unemployment rate.Black or African American.Women.units unicode Percent or rate
[0].data.Unemployment rate.Black or African American.Women.value float 9.8
[0].data.Civilian labor force dict {u'White': {u'All': {u'units': u'Number in thousands', u'value': 75608.0}, u'Men': {u'units': u'Number in thousands', u'value': 43514.0}, u'Women': {u'units': u'Number in thousands', u'value': 25728.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 8334.0}, u'Men': {u'units': u'Number in thousands', u'value': 4180.0}, u'Women': {u'units': u'Number in thousands', u'value': 3498.0}}, u'Asian': {u'All': 0}}
[0].data.Not in labor force dict {u'White': {u'All': 0}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 5998.0}}, u'Asian': {u'All': 0}}
[0].data.Unemployed dict {u'White': {u'All': {u'units': u'Number in thousands', u'value': 4439.0}, u'Men': {u'units': u'Number in thousands', u'value': 2096.0}, u'Women': {u'units': u'Number in thousands', u'value': 1325.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 967.0}, u'Men': {u'units': u'Number in thousands', u'value': 378.0}, u'Women': {u'units': u'Number in thousands', u'value': 343.0}}, u'Asian': {u'All': 0}}
[0].data.Civilian labor force participation rate dict {u'White': {u'All': {u'units': u'Percent or rate', u'value': 59.7}, u'Men': {u'units': u'Percent or rate', u'value': 81.7}, u'Women': {u'units': u'Percent or rate', u'value': 42.7}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 58.1}, u'Men': {u'units': u'Percent or rate', u'value': 76.2}, u'Women': {u'units': u'Percent or rate', u'value': 50.9}}, u'Asian': {u'All': 0}}
[0].data.Unemployment rate dict {u'White': {u'All': {u'units': u'Percent or rate', u'value': 5.9}, u'Men': {u'units': u'Percent or rate', u'value': 4.8}, u'Women': {u'units': u'Percent or rate', u'value': 5.1}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 11.6}, u'Men': {u'units': u'Percent or rate', u'value': 9.0}, u'Women': {u'units': u'Percent or rate', u'value': 9.8}}, u'Asian': {u'All': 0}}
[0].data.Civilian noninstitutional population dict {u'White': {u'All': {u'units': u'Number in thousands', u'value': 126749.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 14332.0}}, u'Asian': {u'All': 0}}
[0].data.Employed dict {u'White': {u'All': {u'units': u'Number in thousands', u'value': 71169.0}, u'Men': {u'units': u'Number in thousands', u'value': 41418.0}, u'Women': {u'units': u'Number in thousands', u'value': 24403.0}}, u'Black or African American': {u'All': {u'units': u'Number in thousands', u'value': 7367.0}, u'Men': {u'units': u'Number in thousands', u'value': 3802.0}, u'Women': {u'units': u'Number in thousands', u'value': 3156.0}}, u'Asian': {u'All': 0}}
[0].data.Employment-population ratio dict {u'White': {u'All': {u'units': u'Percent or rate', u'value': 56.1}, u'Men': {u'units': u'Percent or rate', u'value': 77.7}, u'Women': {u'units': u'Percent or rate', u'value': 40.5}}, u'Black or African American': {u'All': {u'units': u'Percent or rate', u'value': 51.4}, u'Men': {u'units': u'Percent or rate', u'value': 69.3}, u'Women': {u'units': u'Percent or rate', u'value': 45.9}}, u'Asian': {u'All': 0}}
[0].data.Civilian labor force.White dict {u'All': {u'units': u'Number in thousands', u'value': 75608.0}, u'Men': {u'units': u'Number in thousands', u'value': 43514.0}, u'Women': {u'units': u'Number in thousands', u'value': 25728.0}}
[0].data.Civilian labor force.Black or African American dict {u'All': {u'units': u'Number in thousands', u'value': 8334.0}, u'Men': {u'units': u'Number in thousands', u'value': 4180.0}, u'Women': {u'units': u'Number in thousands', u'value': 3498.0}}
[0].data.Civilian labor force.Asian dict {u'All': 0}
[0].data.Civilian labor force.Black or African American.Women.units unicode Number in thousands
[0].data.Civilian labor force.Black or African American.Women.value float 3498.0
[0].data.Unemployed.White dict {u'All': {u'units': u'Number in thousands', u'value': 4439.0}, u'Men': {u'units': u'Number in thousands', u'value': 2096.0}, u'Women': {u'units': u'Number in thousands', u'value': 1325.0}}
[0].data.Unemployed.Black or African American dict {u'All': {u'units': u'Number in thousands', u'value': 967.0}, u'Men': {u'units': u'Number in thousands', u'value': 378.0}, u'Women': {u'units': u'Number in thousands', u'value': 343.0}}
[0].data.Unemployed.Asian dict {u'All': 0}
[0].data.Civilian labor force participation rate.White.Men.units unicode Percent or rate
[0].data.Civilian labor force participation rate.White.Men.value float 81.7
[0].data.Not in labor force.Black or African American.All.units unicode Number in thousands
[0].data.Not in labor force.Black or African American.All.value float 5998.0
[0].data.Unemployed.White.All.units unicode Number in thousands
[0].data.Unemployed.White.All.value float 4439.0
[0].data.Civilian labor force participation rate.Black or African American.All dict {u'units': u'Percent or rate', u'value': 58.1}
[0].data.Civilian labor force participation rate.Black or African American.Men dict {u'units': u'Percent or rate', u'value': 76.2}
[0].data.Civilian labor force participation rate.Black or African American.Women dict {u'units': u'Percent or rate', u'value': 50.9}
[0].data.Employed.Asian.All int 0
[0].data.Not in labor force.Black or African American.All dict {u'units': u'Number in thousands', u'value': 5998.0}
[0].data.Civilian labor force.Black or African American.All dict {u'units': u'Number in thousands', u'value': 8334.0}
[0].data.Civilian labor force.Black or African American.Men dict {u'units': u'Number in thousands', u'value': 4180.0}
[0].data.Civilian labor force.Black or African American.Women dict {u'units': u'Number in thousands', u'value': 3498.0}
[0].data.Civilian labor force.White.Women.units unicode Number in thousands
[0].data.Civilian labor force.White.Women.value float 25728.0
[0].data.Employed.White.All.units unicode Number in thousands
[0].data.Employed.White.All.value float 71169.0
[0].data.Employment-population ratio.White.Men.units unicode Percent or rate
[0].data.Employment-population ratio.White.Men.value float 77.7
[0].data.Employment-population ratio.Black or African American.Men.units unicode Percent or rate
[0].data.Employment-population ratio.Black or African American.Men.value float 69.3
[0].data.Civilian labor force participation rate.White.All dict {u'units': u'Percent or rate', u'value': 59.7}
[0].data.Civilian labor force participation rate.White.Men dict {u'units': u'Percent or rate', u'value': 81.7}
[0].data.Civilian labor force participation rate.White.Women dict {u'units': u'Percent or rate', u'value': 42.7}
[0].data.Employment-population ratio.White.All dict {u'units': u'Percent or rate', u'value': 56.1}
[0].data.Employment-population ratio.White.Men dict {u'units': u'Percent or rate', u'value': 77.7}
[0].data.Employment-population ratio.White.Women dict {u'units': u'Percent or rate', u'value': 40.5}
[0].data.Employed.Black or African American.All dict {u'units': u'Number in thousands', u'value': 7367.0}
[0].data.Employed.Black or African American.Men dict {u'units': u'Number in thousands', u'value': 3802.0}
[0].data.Employed.Black or African American.Women dict {u'units': u'Number in thousands', u'value': 3156.0}
[0].data.Employed.White.All dict {u'units': u'Number in thousands', u'value': 71169.0}
[0].data.Employed.White.Men dict {u'units': u'Number in thousands', u'value': 41418.0}
[0].data.Employed.White.Women dict {u'units': u'Number in thousands', u'value': 24403.0}
[0].data.Civilian labor force participation rate.Black or African American.All.units unicode Percent or rate
[0].data.Civilian labor force participation rate.Black or African American.All.value float 58.1
[0].data.Civilian noninstitutional population.Black or African American.All dict {u'units': u'Number in thousands', u'value': 14332.0}
[0].data.Not in labor force.Asian.All int 0
[0].data.Civilian labor force.Black or African American.Men.units unicode Number in thousands
[0].data.Civilian labor force.Black or African American.Men.value float 4180.0
[0].data.Not in labor force.White.All int 0
[0].data.Employed.White.Men.units unicode Number in thousands
[0].data.Employed.White.Men.value float 41418.0
[0].data.Employment-population ratio.White.Women.units unicode Percent or rate
[0].data.Employment-population ratio.White.Women.value float 40.5