I\'m plotting a categorical variable and instead of showing the counts for each category value.
I\'m looking for a way to get ggplot
to display the perc
Here is a workaround for faceted data. (The accepted answer by @Andrew does not work in this case.) The idea is to calculate the percentage value using dplyr and then to use geom_col to create the plot.
library(ggplot2)
library(scales)
library(magrittr)
library(dplyr)
binwidth <- 30
mtcars.stats <- mtcars %>%
group_by(cyl) %>%
mutate(bin = cut(hp, breaks=seq(0,400, binwidth),
labels= seq(0+binwidth,400, binwidth)-(binwidth/2)),
n = n()) %>%
group_by(cyl, bin) %>%
summarise(p = n()/n[1]) %>%
ungroup() %>%
mutate(bin = as.numeric(as.character(bin)))
ggplot(mtcars.stats, aes(x = bin, y= p)) +
geom_col() +
scale_y_continuous(labels = percent) +
facet_grid(cyl~.)
This is the plot:
If you want percentages on the y-axis and labeled on the bars:
library(ggplot2)
library(scales)
ggplot(mtcars, aes(x = as.factor(am))) +
geom_bar(aes(y = (..count..)/sum(..count..))) +
geom_text(aes(y = ((..count..)/sum(..count..)), label = scales::percent((..count..)/sum(..count..))), stat = "count", vjust = -0.25) +
scale_y_continuous(labels = percent) +
labs(title = "Manual vs. Automatic Frequency", y = "Percent", x = "Automatic Transmission")
When adding the bar labels, you may wish to omit the y-axis for a cleaner chart, by adding to the end:
theme(
axis.text.y=element_blank(), axis.ticks=element_blank(),
axis.title.y=element_blank()
)