Creating dumbbell charts with the ggcharts R package

library(ggcharts)
library(dplyr)
library(gapminder)
data(gapminder)

I am very pleased to announce that my ggcharts package has a new feature: dumbbell_chart().

To showcase this new function I will use the gapminder dataset which contains countries’ population counts from 1952 to 2017. This dataset is in long format. In order for dumbbell_chart() to work properly the data has to be in wide format, though. So, first a bit of data wrangling.

gapminder_wide <- gapminder %>%
  mutate(pop = pop / 1e6) %>%
  filter(year %in% c(1952, 2007)) %>%
  tidyr::pivot_wider(
    id_cols = country,
    names_from = year,
    values_from = pop,
    names_prefix = "pop_"
  )
gapminder_wide
## # A tibble: 142 x 3
##    country     pop_1952 pop_2007
##    <fct>          <dbl>    <dbl>
##  1 Afghanistan    8.43    31.9  
##  2 Albania        1.28     3.60 
##  3 Algeria        9.28    33.3  
##  4 Angola         4.23    12.4  
##  5 Argentina     17.9     40.3  
##  6 Australia      8.69    20.4  
##  7 Austria        6.93     8.20 
##  8 Bahrain        0.120    0.709
##  9 Bangladesh    46.9    150.   
## 10 Belgium        8.73    10.4  
## # ... with 132 more rows

With the data being ready, let’s create a simple chart.

dumbbell_chart(gapminder_wide, country, pop_1952, pop_2007,
               limit = 10)

That looks already quite nice but let’s customize the plot to make it look even better. First, let’s see which customizations can be done by changing the defaults of dumbbell_chart().

chart <- dumbbell_chart(gapminder_wide, country, pop_1952, pop_2007,
                        limit = 10, point_size = 5,
                        point_colors = c("lightgray", "black"),
                        legend_labels = c("1952", "2007"))
chart

To further customize the plot you can use ggplot2 functions.

chart +
  scale_y_continuous(expand = expand_scale(mult = .025)) +
  theme(
    text = element_text(size = 14),
    plot.caption = element_text(family = "mono")
  ) +
  labs(
    title = "The World is Growing",
    subtitle = "Top 10 Most Populated Countries in 2007",
    caption = "Chart created using #ggcharts"
  ) +
  xlab(NULL) +
  ylab("Population (Millions)")


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