Recreating a labelled dumbbell chart in R showing people's openness to the COVID-19 vaccine (CC136)

August 12, 2021 • PD Schloss • 5 min read

In December 2020, Ipsos released a report that contained a labelled dumbbell chart (also called a barbell chart or plot) that showed the percentage of people who said they would likely receive the COVID-19 vaccine once it was available. I thought this was an interesting figure, in part, because of how it depicted paired data. In this episode we’ll recreate the original plot in R so that in future episodes we can modify it and experiment with other ways of representing the data.

Pat uses functions from the tidyverse including functions from the ggplot2, dplyr, ggtext and glue packages in RStudio.

Code

Final R script

library(tidyverse)
library(glue)
library(ggtext)

data <- read_csv("august_october_2020.csv") %>%
  rename(country = X.1,
         percent_august = "Total Agree - August 2020",
         percent_october = "Total Agree - October 2020") %>%
  mutate(bump_august = if_else(percent_august < percent_october,
                               percent_august - 2,
                               percent_august + 2),
         bump_october = if_else(percent_august < percent_october,
                               percent_october + 2,
                               percent_october - 2))

main_plot <- data %>%
  pivot_longer(cols = -country, names_to=c(".value", "month"),
               names_sep = "_") %>%
  mutate(country = factor(country, levels = rev(data$country))) %>%
  ggplot(aes(x=percent, y=country, color=month)) +
  geom_line(color="#e6e6e6", size=1.75, show.legend = FALSE) +
  geom_point(size=2, show.legend = FALSE) +
  geom_text(aes(label=glue("{percent}%"), x=bump),size=3, show.legend = FALSE) +
  scale_color_manual(name=NULL,
                     breaks=c("august", "october"),
                     values=c("#727272", "#15607a"),
                     labels=c("August", "October")) +
  scale_x_continuous(limits=c(50, 100),
                     breaks=seq(50, 100, by=5),
                     labels=glue("{seq(50, 100, 5)}%")) +
  labs(x=NULL, y=NULL,
       title="If a vaccine for COVID-19 were available, I would get it",
       caption="<i>Base: 18,526 online adults aged 16-74 across 15 countries</i><br>Source: Ipsos")+
  theme(
    plot.title.position = "plot",
    plot.title = element_text(face="bold", margin= margin(b=20)),
    plot.caption = element_markdown(hjust=0, color="darkgray"),
    plot.caption.position = "plot",
    panel.background = element_blank(),
    axis.ticks = element_blank(),
    axis.text.x = element_text(color="darkgray"),
    panel.grid.major.x = element_line(color="gray", size=0.1),
    panel.grid.major.y = element_line(color="gray", size=0.1, linetype="dotted")
  )

total <- data %>%
  filter(country == "Total") %>%
  pivot_longer(cols = -country, names_to=c(".value", "month"),
             names_sep = "_") %>%
  mutate(pretty = if_else(month == "august",
                          "Total Agree -<br>August 2020",
                          "Total Agree -<br>October 2020"),
         align = if_else(month == "august", 0, 1))

main_plot +
  coord_cartesian(clip="off") +
  geom_textbox(data=total,
               aes(x=percent, y =country, color=month, label=pretty, hjust=align),
               size=2,
               box.color=NA,
               width=NULL,
               vjust=-0.5,
               box.padding=margin(0,0,0,0),
               fill=NA,
               show.legend=FALSE)

ggsave("august_october_2020_ipsos.tiff", width=6, height=4)

Data

X.1,Total Agree - August 2020,Total Agree - October 2020
Total,77,73
India,87,87
China,97,85
South Korea,84,83
Brazil,88,81
Australia,88,79
United Kingdom,85,79
Mexico,75,78
Canada,76,76
Germany,67,69
Japan,75,69
South Africa,64,68
Italy,67,65
Spain,72,64
United States,67,64
France,59,54
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