Bar plots

Objectives

• This week we’ll learn how to make a number of different bar plots using geom_bar() and our EPI dataset.
• I’ll also show you how to apply some custom colors to your plots, and work through advanced labeling.

Set-up

library(tidyverse)
epi <- readRDS("./data/epir.RDS")

Bar plots

Bar plots are great for visually comparing values of categorical variables. Say you want to use a bar plot to visually compare the population of several countries.

epi_sub <- epi %>%
  filter(country %in% c("China", "India", "United States of America", "Brazil"), year == 2016)

ggplot(epi_sub) +
  geom_bar(aes(x = country, y = POP), stat = "identity") + 
  xlab("") +
  ylab("Population in 2016")

Not a particularly beautiful plot, but we can clearly see that India and China have massive populations compared to the other countries we’ve selected. There are a few things we can do to make this look much better. First, we can reorder the bars by population:

ggplot(epi_sub) +
  geom_bar(aes(x = reorder(country, desc(POP)), y = POP), stat = "identity") +
  xlab("") +
  ylab("Population in 2016") 

For ascending order, just drop the desc() function. Another nice trick is to flip the bar plot to make the axes a bit easier to read:

ggplot(epi_sub) +
  geom_bar(aes(x = reorder(country, POP), y = POP), stat = "identity") +
  xlab("") +
  ylab("Population in 2016") +
  coord_flip()

We can change the fill color, border color, and transparency of all bars as follows:

ggplot(epi_sub) +
  geom_bar(aes(x = reorder(country, POP), y = POP), stat = "identity",
           fill = "dodgerblue", color = "grey40", alpha = 0.5) +
  xlab("") +
  ylab("Population in 2016") +
  coord_flip()

Here, the fill argument refers to the color of the bars, color refers to the line around the bars, and alpha refers to the transparency of the fill.

We can use the scales package to remove the scientific notation on the x-axis and also improve some of our labeling and our theme:

library(scales)
ggplot(epi_sub) +
  geom_bar(aes(x = reorder(country, POP), y = POP), stat = "identity",
           fill = "dodgerblue", color = "grey40", alpha = 0.5) +
  xlab("") +
  ylab("") +
  labs(title = "2016 Population") +
  coord_flip() +
  scale_y_continuous(labels = comma) +
  theme_minimal()