2022 Shootings
Jahnae Edwards | April 28th, 2023
In the wake of the Michigan State shooting, I began thinking about the number of mass shootings that have happened in the United States over the years. I have watched the way that I am educated transform completely due to mass shootings. For this project I wanted to visualize the amount of shootings that have happened in 2022 alone. In order to do this analysis, I found a site called mass shooting archive which has kept track of all mass shootings in the United States since 2014. According to the site, a shooting is considered a mass shooting when more than 4 people are hurt at one location. According to this dataset, in 2022, 647 mass shootings occurred.
To clean this dataset, I began by deleting the last column called "operations" because it is not relevant for this analysis. I then renamed each column and added the column "TotalHurt" which consists of the sum of people killed and injured. A snippet of the cleaned data is shown below.
To visualize this dataset, I used Tableau. Firstly, I wanted to see which states have the most shootings. With this visualization, we can see that nearly every state has had multiple shootings with the most amount of people being hurt/killed being 305 in Illinois.
https://public.tableau.com/app/profile/jahnae4791/viz/FinalVis1/Sheet2?publish=yes
As expected, more populated states like California, Texas, and Florida had more people hurt/killed in 2022, what I found interesting about this, is that Illinois, a state with a much smaller population had the most people injured or killed. This shows that it does not matter where you are, that it is possible to have large mass shootings.
The next fact I wanted to visualize is what months had the most shootings. Using Tableau again, we can see that the summer months had the most people injured from shootings. This is most likely because this is when people gather in large groups the most, making them vulnerable to mass shootings. We can also see that there is no month where there is not a mass shooting, proving the issue we have with guns in this country. Below I included two versions of this visualization, one showing the total hurt/killed and the other showing the differences in the number of people injured versus killed.
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So far we have seen the number of people injured in each state and throughout the year. The final visualization that I completed is counting the number of shootings that have occurred in each state. To create this visualization I used the popular R package called ggplot2. We can see from this visualization that Illinois, California, and Texas had the most shootings and that 38 out of the 50 states had shootings in 2022
Rcode:
ggplot(pt, aes(x = State, y = Shootings)) + geom_bar(stat = "identity") + ggtitle("Mass Shootings by State in 2022") + theme(axis.text.x=element_text(angle=90, hjust=1))
Since I began working on this project, there have been many more mass shootings like the Tate County shooting, killing 6 people, the Memphis shooting, injuring 11 people, and most recently the Nashville shooting killing 5 people. The goal of this visualization was to show how big of an issue mass shootings are in the United States, looking at graphs help to show how big of an issue this is rather than looking at numbers in a dataset. There is no reason that students should be scared to attend school, or people should be afraid to get groceries or go to a public event. My hope is that this visualization can help people realize that something needs to be done about the number of mass shootings occurring in the country. We can see a continuous trend from the time series analysis of shootings constantly happening throughout the year. The solution to this issue is to present graphics like this to policymakers to motivate them to make real changes for our society.
Sources:
Click
here for the dataset
Click
here for 2023 shootings
R code:
library(dplyr)
library(ggplot2)
library(lubridate)
df <- read.csv("export-d4bb0a29-dd36-44f4-9a26-3615ceda557a.csv")
#Clean the data
df <- df[,-8]
colnames(df) <- c("ID", "Date", "State", "Location", "Address", "Killed", "Injured")
TotalHurt <- df$Killed + df$Injured
df <- cbind(df, TotalHurt)
#new dataframe
pt <- table(df$State)
pt <- as.data.frame(pt)
colnames(pt) <- c("State", "Shootings")
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