knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
Focuses on creating data sets and other tools that help make understanding gerrymandering faster and easier. Designed for easy preparation to run simulation analysis with the R package redist, but is aimed at the geographic aspects of redistricting, not partitioning methods. Most of these tools are gathered from seminar papers and do not correspond to a single publication.
You can install the released version of geomander from CRAN with:
install.packages("geomander")
And the development version from GitHub with:
# install.packages("devtools") devtools::install_github("christopherkenny/geomander")
A very common task is aggregating block data to precincts.
library(geomander) library(tidyverse) # load precincts data('va18sub') # create block data block <- create_block_table(state = 'VA', county = '087') # match the geographies matches <- geo_match(from = block, to = va18sub) # Aggregate prec <- block2prec(block_table = block, matches = matches)
Other important tasks include breaking data into pieces by blocks underlying them.
library(geomander) library(tidyverse) # load precincts data("va18sub") # subset to target area va18sub <- va18sub %>% filter(COUNTYFP == '087')
Then we can get common block data:
block <- create_block_table(state = 'VA', county = '087')
And estimate down to blocks
disagg <- geo_estimate_down(from = va18sub, to = block, wts = block$vap, value = va18sub$G18USSRSTE)
For more information, see the documentation and vignettes, available at https://christophertkenny.com/geomander/
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