R/stl_race_income_point.R
stl_race_income_point.RdA simple features data set containing the geometry and associated attributes for the 2013-2017 American Community Survey estimates for median household income and the percentage of white residents in St. Louis. This version of the sample data are stored as point data.
data(stl_race_income_point)A data frame with 106 rows and 4 variables:
full GEOID string
Percent of white residents per tract
Median household income of tract
simple features geometry
tidycensus package
str(stl_race_income_point)
#> Classes ‘sf’ and 'data.frame': 106 obs. of 4 variables:
#> $ GEOID : chr "29510102300" "29510102400" "29510104500" "29510106100" ...
#> $ pctWhite: num 82.93 90.12 74.72 1.75 2.38 ...
#> $ medInc : num 51650 45375 54286 18895 36130 ...
#> $ geometry:sfc_POINT of length 106; first list element: 'XY' num -90.3 38.6
#> - attr(*, "sf_column")= chr "geometry"
#> - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA
#> ..- attr(*, "names")= chr [1:3] "GEOID" "pctWhite" "medInc"
head(stl_race_income_point)
#> Simple feature collection with 6 features and 3 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -90.28881 ymin: 38.56287 xmax: -90.27698 ymax: 38.6694
#> Geodetic CRS: NAD83
#> GEOID pctWhite medInc geometry
#> 1 29510102300 82.925682 51650 POINT (-90.28698 38.56287)
#> 2 29510102400 90.116046 45375 POINT (-90.27785 38.57716)
#> 3 29510104500 74.723618 54286 POINT (-90.28087 38.62656)
#> 4 29510106100 1.752464 18895 POINT (-90.28116 38.6694)
#> 5 29510105500 2.376729 36130 POINT (-90.27698 38.66003)
#> 6 29510105200 36.833277 60938 POINT (-90.28881 38.65056)
summary(stl_race_income_point$medInc)
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 10545 23474 34688 37140 51379 74425