How to create a population pyramid with ggplot2

Problem

We want to create a population pyramid with ggplot2. Our example is the Spanish population by age and gender in 2020.

Example

# A tibble: 42 x 3
   Age      Gender   Total
           
 1 "0-4 "   male   1018039
 2 "0-4 "   female  963653
 3 "5-9"    male   1196380
 4 "5-9"    female 1129063
 5 "10-14"  male   1297635
 6 "10-14"  female 1225863
 7 "15-19 " male   1232566
 8 "15-19 " female 1156455
 9 "20-24 " male   1207902
10 "20-24 " female 1152765
# ... with 32 more rows

df <- structure(list(Age = c("0-4 ", "0-4 ", "5-9", "5-9", "10-14", 
"10-14", "15-19 ", "15-19 ", "20-24 ", "20-24 ", "25-29 ", "25-29 ", 
"30-34 ", "30-34 ", "35-39 ", "35-39 ", "40-44 ", "40-44 ", "45-49 ", 
"45-49 ", "50-54 ", "50-54 ", "55-59 ", "55-59 ", "60-64 ", "60-64 ", 
"65-69 ", "65-69 ", "70-74 ", "70-74 ", "75-79 ", "75-79 ", "80-84 ", 
"80-84 ", "85-89 ", "85-89 ", "90-94 ", "90-94 ", "95-99 ", "95-99 ", 
"100+", "100+"), Gender = c("male", "female", "male", "female", 
"male", "female", "male", "female", "male", "female", "male", 
"female", "male", "female", "male", "female", "male", "female", 
"male", "female", "male", "female", "male", "female", "male", 
"female", "male", "female", "male", "female", "male", "female", 
"male", "female", "male", "female", "male", "female", "male", 
"female", "male", "female"), Total = c(1018039L, 963653L, 1196380L, 
1129063L, 1297635L, 1225863L, 1232566L, 1156455L, 1207902L, 1152765L, 
1308197L, 1275776L, 1421558L, 1417845L, 1702135L, 1688865L, 2024303L, 
1971909L, 1968659L, 1926866L, 1828015L, 1840434L, 1652558L, 1712299L, 
1410111L, 1502563L, 1153768L, 1270544L, 1020478L, 1191698L, 773823L, 
974046L, 513692L, 759379L, 361702L, 634714L, 133032L, 302885L, 
27305L, 84007L, 3732L, 13576L)), class = "data.frame", row.names = c(NA, 
-42L))
tibble(df)

Solution

First we need to create two columns. One to convert male population to negative so it is reversed in the plot. Another column with the population percentage by age and sex.

df <- df %>%
  group_by(Gender) %>% 
  mutate(
    Population = ifelse(Gender == "female", Total,-Total),
    Percent = ifelse(Gender == "female", 100 * (Total / sum(Total)),-100 * (Total / sum(Total))))
df$Age <- factor(df$Age, levels=unique(df$Age)) # To keep the original order of the character vector

Absolute numbers

ggplot(df, aes(x = Age, Population, fill = Gender)) + 
  geom_bar(data = filter(df, Gender == "female"), stat = "identity") + 
  geom_bar(data = filter(df, Gender == "male"),  stat = "identity") + 
  scale_y_continuous(breaks = seq(-2000000, 2000000, 500000), labels = comma(abs(seq(-2000000, 2000000, 500000))))+
  coord_flip()

Percentage

ggplot(df, aes(x = Age, Percent, fill = Gender)) +
  geom_bar(data = filter(df, Gender == "female"), stat = "identity") +
  geom_bar(data = filter(df, Gender == "male"),  stat = "identity") +
  scale_y_continuous(breaks = seq(-10, 10, 2), labels = comma(abs(seq(-10, 10, 2)))) +
  coord_flip()

References

• stackoverflow
• Population series from INE (Spanish Statistical Office)