Recreate the Voter Registration Graphic

Voter Registrations Are Way, Way Down During the Pandemic

FiveThirtyEight article (Jun 26, 2020) by Kaleigh Rogers and Nathaniel Rakich

The original article can be found at:

https://fivethirtyeight.com/features/voter-registrations-are-way-way-down-during-the-pandemic/

Tasks

• Identify/implement the major geometry (or geometries) used
• Identify/implement the main components of the aesthetic mapping (color, size, shape, transparency, ..)
• Identify/implement any transformations on the scales or axes and using faceting, when necessary
• Label the axes and providing a title

Accessing the Data

# Load the tidyverse 
library(tidyverse)

# Import data 
vreg<-read.csv("https://raw.githubusercontent.com/fivethirtyeight/data/master/voter-registration/new-voter-registrations.csv",
header=TRUE)

Hints/Tips

1. Relevel the data

# Level the Month variable so that its in the right order (ie not alphabetical)
vreg$Month<-factor(vreg$Month,
                   levels=c("Jan", "Feb", "Mar", "Apr", "May"))

2. Tidy the data

### USE spread() FROM tidyr 

vregYear<-vreg%>%
spread(Year, New.registered.voters)

### RENAME THE COLUMNS
colnames(vregYear)<-c("Jurisdiction", "Month", "Y2016", "Y2020")

3. Mutate to add the change

### mutate() FROM dplyr() 
vregChange<-vregYear%>%
mutate(change=Y2020-Y2016)

4. Other hints

• You can add another column to define color

vregChange<-vregYear%>%
  mutate(change=Y2020-Y2016)%>%
  mutate(direction=change>=0)

• Pay careful attention to the axes, you might want to read the help file for facet_wrap

Final Product

The code has been hidden, however, your final graphic should look like this: