library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(ggplot2)
# get data from rcfss package
# install latest version if not already installed
# devtools::install_github("uc-cfss/rcfss")
library(rcfss)
# load the data
data("mass_shootings")
mass_shootings
#> # A tibble: 125 × 14
#> case year month day location summary fatalities injured total_victims
#> <chr> <dbl> <chr> <int> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 Oxford H… 2021 Nov 30 Oxford,… "Ethan… 4 7 11
#> 2 San Jose… 2021 May 26 San Jos… "Samue… 9 0 9
#> 3 FedEx wa… 2021 Apr 15 Indiana… "Brand… 8 7 15
#> 4 Orange o… 2021 Mar 31 Orange,… "Amina… 4 1 5
#> 5 Boulder … 2021 Mar 22 Boulder… "Ahmad… 10 0 10
#> 6 Atlanta … 2021 Mar 16 Atlanta… "Rober… 8 1 9
#> 7 Springfi… 2020 Mar 16 Springf… "Joaqu… 4 0 4
#> 8 Molson C… 2020 Feb 26 Milwauk… "Antho… 5 0 5
#> 9 Jersey C… 2019 Dec 10 Jersey … "David… 4 3 7
#> 10 Pensacol… 2019 Dec 6 Pensaco… "Ahmed… 3 8 11
#> # … with 115 more rows, and 5 more variables: location_type <chr>, male <lgl>,
#> # age_of_shooter <dbl>, race <chr>, prior_mental_illness <chr>
# Generate a bar chart that identifies the number of mass shooters
# associated with each race category. The bars should be sorted
# from highest to lowest.
# using reorder() and aggregating the data before plotting
mass_shootings %>%
count(race) %>%
drop_na(race) %>%
ggplot(mapping = aes(x = reorder(race, -n), y = n)) +
geom_col() +
labs(
title = "Mass shootings in the United States (1982-2019)",
x = "Race of perpetrator",
y = "Number of incidents"
)
#> Error in drop_na(., race): could not find function "drop_na"
Created on 2022-07-05 by the reprex package (v2.0.1)