This library comes from FiveThirtyEight's story on earnings of college majors based on data from the American Community Survey 2010-2012 Public Use Microdata Series. Included is information about employment numbers, major information, and the earnings of different majors.


Explore Structure

Index Type Example Value
0 dict { }
... ... ...
Key Type Example Value Comment
"Major Information" dict { }
"Demographics" dict { }
"Employment" dict { }
"Earnings" dict { }
Key Type Example Value Comment
"Median Earnings" int 110000
"75th Percentile of Earnings" int 125000
"25th Percentile of Earnings" int 95000
Key Type Example Value Comment
"Men" int 2057
"Women as Share of Total" float 0.120564344
"Women" int 282
Key Type Example Value Comment
"Major Code" int 2419
"Rank by Median Earnings" int 1
"Total Number in Major" int 2339
"Major Category" str "Engineering"
Key Type Example Value Comment
"Non-College Jobs" int 364
"College Jobs" int 1534
"Earnings Breakdown" dict { }
"Low Wage Jobs" int 193
Key Type Example Value Comment
"Part Time" int 270
"Unemployed" int 37
"Unemployment Rate" float 0.018380527
"Full Time" int 1849
"Employed" int 1976
"Full Time, Year-Round" int 1207


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This library has 1 function you can use.
import graduates
list_of_grad_major = graduates.get_majors()



Returns information about all recorded majors.