The raw data behind the story "The Economic Guide To Picking A College Major" https://fivethirtyeight.com/features/the-economic-guide-to-picking-a-college-major/.

college_recent_grads

Format

A data frame with 173 rows representing majors (recent graduates) and 21 variables:

rank

Rank by median earnings

major_code

Major code, FO1DP in ACS PUMS

major

Major description

major_category

Category of major from Carnevale et al

total

Total number of people with major

sample_size

Sample size (unweighted) of full-time, year-round ONLY (used for earnings)

men

Men with major

women

Women with major

sharewomen

Proportion women

employed

Number employed (ESR == 1 or 2)

employed_fulltime

Employed 35 hours or more

employed_parttime

Employed less than 35 hours

employed_fulltime_yearround

Employed at least 50 weeks (WKW == 1) and at least 35 hours (WKHP >= 35)

unemployed

Number unemployed (ESR == 3)

unemployment_rate

Unemployed / (Unemployed + Employed)

p25th

25th percentile of earnings

median

Median earnings of full-time, year-round workers

p75th

75th percentile of earnings

college_jobs

Number with job requiring a college degree

non_college_jobs

Number with job not requiring a college degree

low_wage_jobs

Number in low-wage service jobs

Source

See https://github.com/fivethirtyeight/data/blob/master/college-majors/readme.md. Note that women-stem.csv was a subset of the original recent-grads.csv, so no data frame was created.

See also