bg.pts: Block group internal points from Census Bureau for 2020...

In ejanalysis/proxistat: Create a Proximity Score in Each Census Unit, Based on Distances to Specified Points (as in EPA's EJScreen tool, for example)

Block group internal points from Census Bureau for 2020 geographies

Description

The population weighted mean of block internal points, within each block group.

Format

A data.frame of block groups, with these variables:

'data.frame':	242335 obs. of  5 variables:
 $ FIPS      : chr  "010010201001" "010010201002" "010010202001" "010010202002" ...
 $ lat       : num  32.5 32.5 32.5 32.5 32.5 ...
 $ lon       : num  -86.5 -86.5 -86.5 -86.5 -86.5 ...
 $ bgid      : int  1 2 3 4 5 6 7 8 9 10 ...
 $ blockcount: int  26 30 14 27 21 21 16 29 29 18 ...
 - attr(*, "census_version")= num 2020
 - attr(*, "acs_version")= chr "2016-2020"
 - attr(*, "acs_releasedate")= chr "3/17/2022"
 - attr(*, "ejscreen_version")= chr "2.1"
 - attr(*, "ejscreen_releasedate")= chr "October 2022"
 - attr(*, "ejscreen_pkg_data")= chr "bg22"

Details

This data set provides a data.frame with 242,335 block groups, with 5 variables. It has PR but lacks "AS" "GU" "MP" "VI" The population weighted mean not spatial mean was used to summarize the lat lon values of all Census 2020 blocks in a given block group.

Source

Derived from Census Bureau, obtained 10/2022. bg.pts <- as.data.frame(copy(EJAM::bgpts)) # see EJAM package for details names(bg.pts) <- c('bgid', 'lat','lon','FIPS','blockcount') bg.pts <- bg.pts[ , c('FIPS', 'lat', 'lon', 'bgid', 'blockcount')] bg.pts <- metadata_add(bg.pts) usethis::use_data(bg.pts)

See Also

EJAM::proxistat2 EJAM::bgpts and acs and for older data UScensus2010blocks

ejanalysis/proxistat documentation built on Jan. 1, 2025, 10:02 a.m.