Awesome-Agent-Skills-for-Empirical-Research redistricting-analysis

Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.

install

source · Clone the upstream repo

git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/22-christopherkenny-skills/skills/redistricting-analysis" ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-redistricting-ana && rm -rf "$T"

manifest: skills/22-christopherkenny-skills/skills/redistricting-analysis/SKILL.md

source content

Redistricting Analysis with the redistverse

A comprehensive reference for redistricting analysis in R using the redistverse ecosystem (

library(redistverse)

loads

redist

redistmetrics

ggredist

geomander

sf

, and

adj

Standard Analysis Pipeline

Load data — Download pre-built precinct map + demographics + elections via
```
alarmdata
```
, or assemble your own
```
sf
```
object and build a
```
redist_map
```
. → 12-alarmdata.md
Prepare adjacency — Verify and edit the adjacency graph (remove water-body edges, fix topological errors). → 08-adj.md, 09-geomander-adjacency.md
Set constraints — Define population tolerance, county-split penalties, VRA hinge constraints, compactness. → 02-redist-constraints.md
Simulate — Run
```
redist_smc()
```
(recommended) or MCMC to generate an ensemble of valid plans. → 01-redist-simulation.md
Validate — Check convergence (
```
summary()
```
), R-hat, effective sample size, and plan diversity. → 01-redist-simulation.md
Score — Compute compactness, partisan fairness, splits, and other metrics across the ensemble. → 04–06 redistmetrics references
Visualize & compare — Map plans, plot metric distributions, compare enacted plan to the baseline. → 07-ggredist.md

Quick Navigation

Package / Topic	Reference
`redist_map` , `redist_smc` , `redist_mergesplit` , `redist_flip` , `redist_plans` , diagnostics	01-redist-simulation.md
`redist_constr` , `add_constr_splits` , `add_constr_grp_hinge` , all soft constraints	02-redist-constraints.md
`redist_enumpart` , `redist_shortburst` , `redist_cyclewalk` , `init_particles`	03-redist-advanced.md
`redistmetrics` — Polsby-Popper, Reock, spanning tree, `prep_perims` , `comp_*` functions	04-redistmetrics-compactness.md
`redistmetrics` — efficiency gap, mean-median, bias, declination, `part_*` functions	05-redistmetrics-partisan.md
`redistmetrics` — county splits, segregation, competitiveness, incumbents, `plan_parity` , `group_frac`	06-redistmetrics-other.md
`ggredist` — `geom_district` , party color scales, cartographic palettes, `theme_map`	07-ggredist.md
`adj` — adjacency graph construction, edge operations, coloring, Laplacian	08-adj.md
`geomander` — adjacency construction, contiguity checks, `seam_rip` , edge editing	09-geomander-adjacency.md
`geomander` — `geo_match` , `estimate_down/up` , `block2prec` , spatial estimation	10-geomander-spatial.md
`geomander` — downloading VEST, ALARM, DRA, HEDA, `get_lewis` election data	11-geomander-data.md
`alarmdata` — `alarm_50state_map` , pre-built datasets, caching, `alarm_add_plan`	12-alarmdata.md
`PL94171` — Census P.L. 94-171 decennial data ingestion	13-pl94171.md
`censable` (data + state IDs), `easycensus` (ACS), `tinytiger` (TIGER shapefiles)	14-census-utilities.md
`baf` — download official Census Bureau block assignment files	15-baf.md
`rict` — `gt` summary tables: population, demographics, elections, compactness, splits	16-rict.md
`redistio` — interactive Shiny plan drawing ( `draw()` ) and adjacency editor ( `adj_editor()` )	17-redistio.md

Key Data Structures

redist_map

— an

sf

tibble with one row per precinct. Stores the adjacency graph, population column, number of districts, and population tolerance. Created by

redist_map()

or downloaded via

alarm_50state_map()

. Standard columns include

pop

pop_black

pop_hisp

pop_asian

pop_white

pop_vap

pop_bvap

ndv

(Democratic votes),

nrv

(Republican votes), and

geometry

redist_plans

— a tibble with one row per district per plan (so

nsims × ndists

rows, plus reference plans). Stores district assignments in a hidden integer matrix; metrics are added as columns via

mutate()

. Access the plan matrix with

get_plans_matrix()

adj

— an S3 vector class representing an adjacency list. Each element is a zero-indexed integer vector of neighbors. Stored as the

adj

column in

redist_map

Population Tolerance Guidelines

Map type	Typical `pop_tol`	Legal basis
Congressional	`0.005` (±0.5%)	Wesberry v. Sanders
State legislative	`0.05` (±10%)	Reynolds v. Sims
Local	Varies by state	State law