A dataset containing median individual earnings by various dimensions (education, occupation, etc.) for the US and Maryland, for adults ages 25 and up with positive earnings. The data is calculated from the 2021 American Community Survey (ACS) Public Use Microdata Sample (PUMS) data via the Integrated Public Use Microdata Series (IPUMS).
Format
A data frame with 309 rows and 15 variables:
- dimension
Factor. The dimension across which values are calculated.
- name
Factor. The name of the region (US or Maryland).
- sex
Factor. The sex of the individuals.
- race_eth
Factor. The race/ethnicity of the individuals.
- edu
Factor. The education level of the individuals.
- occ_group
Factor. The occupation group of the individuals.
- univ
Factor. Universe of workers, whether the denominator is all workers or full-time only.
- is_fulltime
Logical. Whether the individual is a full-time worker.
NAif distinction isn't included.- count
Numeric. The number of individuals in the group.
- earn_q20
Numeric. The 20th percentile of earnings.
- earn_q25
Numeric. The 25th percentile of earnings.
- earn_q50
Numeric. The 50th percentile (median) earnings.
- earn_q75
Numeric. The 75th percentile of earnings.
- earn_q80
Numeric. The 80th percentile of earnings.
- sample_n
Numeric. The sample size.
Source
U.S. Census Bureau, American Community Survey, Integrated Public Use Microdata Series https://usa.ipums.org/usa/. Analyzed using the srvyr package.
Examples
head(wages)
#> # A tibble: 6 × 15
#> dimension name sex race_eth edu occ_group univ is_fulltime count
#> <fct> <fct> <fct> <fct> <fct> <fct> <fct> <lgl> <dbl>
#> 1 total US Total Total Total Total All work… NA 1.49e8
#> 2 total Maryland Total Total Total Total All work… NA 2.98e6
#> 3 sex US Men Total Total Total Full-tim… TRUE 6.02e7
#> 4 sex Maryland Men Total Total Total Full-tim… TRUE 1.21e6
#> 5 sex US Men Total Total Total All work… NA 7.89e7
#> 6 sex Maryland Men Total Total Total All work… NA 1.53e6
#> # ℹ 6 more variables: earn_q20 <dbl>, earn_q25 <dbl>, earn_q50 <dbl>,
#> # earn_q75 <dbl>, earn_q80 <dbl>, sample_n <dbl>