# geomander

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.

## Installation

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")``````

## Examples

A very common task is aggregating block data to precincts.

``````library(geomander)
library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
#> ✔ ggplot2 3.3.6     ✔ purrr   0.3.4
#> ✔ tibble  3.1.8     ✔ dplyr   1.0.9
#> ✔ tidyr   1.2.0     ✔ stringr 1.4.1
#> ✔ readr   2.1.2     ✔ forcats 0.5.1
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──

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)

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)``