alarm_50state {alarmdata} | R Documentation |
These functions will download redist_map and
redist_plans objects for the 50-State Simulation
Project from the ALARM Project's Dataverse. alarm_50state_doc()
will
download documentation for a particular state and show it in a browser.
alarm_50state_stats
will download just the summary statistics for a state.
alarm_50state_map(state, year = 2020, refresh = FALSE)
alarm_50state_plans(
state,
stats = TRUE,
year = 2020,
refresh = FALSE,
compress = "xz"
)
alarm_50state_stats(state, year = 2020, refresh = FALSE)
alarm_50state_doc(state, year = 2020)
state |
A state name, abbreviation, FIPS code, or ANSI code. |
year |
The redistricting cycle to download. Currently only |
refresh |
If |
stats |
If |
compress |
The compression level used for caching redist_plans objects. |
Every decade following the Census, states and municipalities must redraw districts for Congress, state houses, city councils, and more. The goal of the 50-State Simulation Project is to enable researchers, practitioners, and the general public to use cutting-edge redistricting simulation analysis to evaluate enacted congressional districts.
Evaluating a redistricting plan requires analysts to take into account each state’s redistricting rules and particular political geography. Comparing the partisan bias of a plan for Texas with the bias of a plan for New York, for example, is likely misleading. Comparing a state’s current plan to a past plan is also problematic because of demographic and political changes over time. Redistricting simulations generate an ensemble of alternative redistricting plans within a given state which are tailored to its redistricting rules. Unlike traditional evaluation methods, therefore, simulations are able to directly account for the state’s political geography and redistricting criteria.
For alarm_50state_map()
, a redist_map. For
alarm_50state_plans()
, a redist_plans. For
alarm_50state_doc()
, invisibly returns the path to the HTML documentation,
and also loads an HTML file into the viewer or web browser.
For alarm_50state_stats()
, a tibble.
# requires Harvard Dataverse API key
alarm_50state_map("WA")
alarm_50state_plans("WA", stats = FALSE)
alarm_50state_stats("WA")
alarm_50state_doc("WA")
map <- alarm_50state_map("WY")
pl <- alarm_50state_plans("WY")