R/data-mn_police_use_of_force.R

In OpenIntroStat/openintro: Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

#' Minneapolis police use of force data.
#'
#' From Minneapolis, data from 2016 through August 2021
#'
#' @name mn_police_use_of_force
#' @docType data
#' @format A data frame with 12925 rows and 13 variables.
#' \describe{
#'   \item{response_datetime}{DateTime of police response.}
#'   \item{problem}{Problem that required police response.}
#'   \item{is_911_call}{Whether response was iniated by call to 911.}
#'   \item{primary_offense}{Offense of subject.}
#'   \item{subject_injury}{Whether subject was injured Yes/No/null.}
#'   \item{force_type}{Type of police force used.}
#'   \item{force_type_action}{Detail of police force used.}
#'   \item{race}{Race of subject.}
#'   \item{sex}{Gender of subject.}
#'   \item{age}{Age of subject.}
#'   \item{type_resistance}{Resistance to police by subject.}
#'   \item{precinct}{Precinct where response occurred.}
#'   \item{neighborhood}{Neighborhood where response occurred.}
#' }
#' @examples
#' library(dplyr)
#' library(ggplot2)
#'
#' # List percent of total for each race
#' mn_police_use_of_force |>
#'   count(race) |>
#'   mutate(percent = round(n / sum(n) * 100, 2)) |>
#'   arrange(desc(percent))
#'
#' # Display use of force count by three races
#' race_sub <- c("Asian", "White", "Black")
#' ggplot(
#'   mn_police_use_of_force |> filter(race %in% race_sub),
#'   aes(force_type, ..count..)
#' ) +
#'   geom_point(stat = "count", size = 4) +
#'   coord_flip() +
#'   facet_grid(race ~ .) +
#'   labs(
#'     x = "Force Type",
#'     y = "Number of Incidents"
#'   )
#' @source [Minneapolis](https://opendata.minneapolismn.gov/search?groupIds=79606f50581f4a33b14a19e61c4891f7)
"mn_police_use_of_force"