rict
Redistricting in Clean Tables
Provides a suite of tools to create tables that accompany maps. The tools create clean, informative tables for electoral outcomes, compactness, and other district-level quantities. Most tools are aimed at the redistricting context, but are broadly applicable to other electoral data.
rict 
rict provides clean, formatted gt tables
to accompany redistricting maps. It is designed to complement
redist and
redistmetrics, but works
with any electoral or demographic data.
Installation
You can install the development version of rict from
GitHub with:
pak::pak('christopherkenny/rict')
Overview
rict provides a family of rict_*() functions, each producing a
formatted table for a specific redistricting quantity:
| Function | Description |
|---|---|
rict() |
District-level summary from a redist_map or redist_plans |
rict_demographics() |
Population and voting-age population by race/ethnicity |
rict_elections() |
Democratic vote shares across electoral contests |
rict_compactness() |
Common compactness scores (Polsby-Popper, Reock, etc.) |
rict_population() |
Population and deviation from the ideal district size |
rict_splits() |
Number of administrative units split by the plan |
rict_contiguity() |
Number of contiguous pieces per district |
Additional helpers embed visuals directly inside a gt table:
| Function | Description |
|---|---|
gt_plot_sf() |
Embed district map thumbnails |
gt_plot_compactness() |
Embed compactness geometry plots |
Examples
Demographics
rict_demographics() summarizes total population and voting-age
population by race/ethnicity across districts.
library(rict)
rict_demographics(map = wv, plan = wv$cd_2020)
Compactness
rict_compactness() tabulates common geometric compactness scores for
each district.
rict_compactness(map = wv, plan = wv$cd_2020)
Elections
rict_elections() shows Democratic vote shares for each electoral
contest, along with normal partisan averages.
rict_elections(map = wv, plan = wv$cd_2020)
Plans
For a redist_plans object, rict() formats a single draw as a table.
data(wv_plans)
rict(wv_plans, 'cd_2020')
