> 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: 114 x 14
> case year month day location summary fatalities injured total_victims
>
> 1 Dayt… 2019 Aug 4 Dayton,… "PENDI… 9 27 36
> 2 El P… 2019 Aug 3 El Paso… "PENDI… 20 26 46
> 3 Gilr… 2019 Jul 28 Gilroy,… "Santi… 3 12 15
> 4 Virg… 2019 May 31 Virgini… "DeWay… 12 4 16
> 5 Harr… 2019 Feb 15 Aurora,… "Gary … 5 6 11
> 6 Penn… 2019 Jan 24 State C… "Jorda… 3 1 4
> 7 SunT… 2019 Jan 23 Sebring… "Zephe… 5 0 5
> 8 Merc… 2018 Nov 19 Chicago… "Juan … 3 0 3
> 9 Thou… 2018 Nov 7 Thousan… "Ian D… 12 22 34
> 10 Tree… 2018 Oct 27 Pittsbu… "Rober… 11 6 17
> # … with 104 more rows, and 5 more variables: location_type , male ,
> # age_of_shooter , race , prior_mental_illness
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"
Copy the code below to generate a reproducible example
using the reprex package. Once you generate it, post it on
https://github.com/uc-cfss/Discussion/issues/180
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: 114 x 14
> case year month day location summary fatalities injured total_victims
>
> 1 Dayt… 2019 Aug 4 Dayton,… "PENDI… 9 27 36
> 2 El P… 2019 Aug 3 El Paso… "PENDI… 20 26 46
> 3 Gilr… 2019 Jul 28 Gilroy,… "Santi… 3 12 15
> 4 Virg… 2019 May 31 Virgini… "DeWay… 12 4 16
> 5 Harr… 2019 Feb 15 Aurora,… "Gary … 5 6 11
> 6 Penn… 2019 Jan 24 State C… "Jorda… 3 1 4
> 7 SunT… 2019 Jan 23 Sebring… "Zephe… 5 0 5
> 8 Merc… 2018 Nov 19 Chicago… "Juan … 3 0 3
> 9 Thou… 2018 Nov 7 Thousan… "Ian D… 12 22 34
> 10 Tree… 2018 Oct 27 Pittsbu… "Rober… 11 6 17
> # … with 104 more rows, and 5 more variables: location_type, male ,
> # age_of_shooter, race , prior_mental_illness
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"