Population pyramid plot with ggplot2 and dplyr (instead of plyr)

Question

I am trying to reproduce the simple population pyramid from the post Simpler population pyramid in ggplot2

using ggplot2 and dplyr (instead of plyr).

Here is the original example with plyr and a seed

set.seed(321)
test <- data.frame(v=sample(1:20,1000,replace=T), g=c('M','F'))

require(ggplot2)
require(plyr)    
ggplot(data=test,aes(x=as.factor(v),fill=g)) + 
  geom_bar(subset=.(g=="F")) + 
  geom_bar(subset=.(g=="M"),aes(y=..count..*(-1))) + 
  scale_y_continuous(breaks=seq(-40,40,10),labels=abs(seq(-40,40,10))) + 
  coord_flip()

Works fine.

But how can I generate this same plot with dplyr instead? The example uses plyr in the subset = .(g == statements.

I have tried the following with dplyr::filter but got an error:

require(dplyr)
ggplot(data=test,aes(x=as.factor(v),fill=g)) + 
  geom_bar(dplyr::filter(test, g=="F")) + 
  geom_bar(dplyr::filter(test, g=="M"),aes(y=..count..*(-1))) + 
  scale_y_continuous(breaks=seq(-40,40,10),labels=abs(seq(-40,40,10))) + 
  coord_flip()

Error in get(x, envir = this, inherits = inh)(this, ...) : 
  Mapping should be a list of unevaluated mappings created by aes or aes_string

score 6 · Accepted Answer · answered Aug 08 '15 at 21:58

You avoid the error by specifying the argument data in geom_bar:

ggplot(data = test, aes(x = as.factor(v), fill = g)) + 
  geom_bar(data = dplyr::filter(test, g == "F")) + 
  geom_bar(data = dplyr::filter(test, g == "M"), aes(y = ..count.. * (-1))) + 
  scale_y_continuous(breaks = seq(-40, 40, 10), labels = abs(seq(-40, 40, 10))) + 
  coord_flip()

score 5 · Answer 2 · edited May 23 '17 at 11:54

5

You can avoid both dplyr and plyr when making population pyramids with recent versions of ggplot2.

If you have counts of the sizes of age-sex groups then use the answer here

If your data is at the individual level (as yours is) then use the following:

set.seed(321)
test <- data.frame(v=sample(1:20,1000,replace=T), g=c('M','F'))
head(test)
#    v g
# 1 20 M
# 2 19 F
# 3  5 M
# 4  6 F
# 5  8 M
# 6  7 F

library("ggplot2")
ggplot(data = test, aes(x = as.factor(v), fill = g)) + 
  geom_bar(data = subset(test, g == "F")) + 
  geom_bar(data = subset(test, g == "M"), 
           mapping = aes(y = - ..count.. ),
           position = "identity") +
  scale_y_continuous(labels = abs) +
  coord_flip()

edited May 23 '17 at 11:54

Community

1
1

answered May 09 '16 at 07:51

guyabel

8,014
6
57
86

I get similar result except that the y axis is not ordered.... (it is actually ordered by alphabetical order: 1,10,11,12,13,14,15,16,17,18,19,2,20,21,...) – RockScience Jan 26 '17 at 07:27
1

replacing `as.factor(v)` by `v` worked: now it is in the right order – RockScience Jan 26 '17 at 07:29
1

@gjabel can you convert the count to percent with this approach? – Prometheus Apr 05 '17 at 15:17

score 0 · Answer 3 · answered Aug 14 '20 at 20:09

To build an Age Pyramid with individual data or microdata you can use:

test <- data.frame(v=sample(1:100, 1000, replace=T), g=c('M','F'))

ggplot(data = test, aes(x = v, fill = g)) + 
  geom_histogram(data = subset(test, g == "F"), binwidth = 5, color="white", position = "identity") +
  geom_histogram(data = subset(test, g == "M"), binwidth = 5, color="white", position = "identity", 
                 mapping = aes(y = - ..count.. )) +
  scale_x_continuous("Age", breaks = c(seq(0, 100, by=5))) +
  scale_y_continuous("Population", breaks = seq(-30, 30, 10), labels = abs) +
  scale_fill_discrete(name = "Sex") +
  coord_flip() +
  theme_bw()

Changing the binwidth in geom_histogram() can group your data in wider categories.

Changing binwidth to 10 and adjusting the axis breaks:

ggplot(data = test, aes(x = v, fill = g)) + 
  geom_histogram(data = subset(test, g == "F"), binwidth = 10, color="white", position = "identity") +
  geom_histogram(data = subset(test, g == "M"), binwidth = 10, color="white", position = "identity", 
                 mapping = aes(y = - ..count.. )) +
  scale_x_continuous("Age", breaks = c(seq(0, 100, by = 10))) +
  scale_y_continuous("Population", breaks = seq(-100, 100, 10), labels = abs) +
  scale_fill_discrete(name = "Sex") +
  coord_flip() +
  theme_bw()

Population pyramid plot with ggplot2 and dplyr (instead of plyr)

3 Answers3

Linked