I'm looking for a way to label a stacked bar chart with percentages while the y-axis shows the original count (using ggplot). Here is a MWE for the plot without labels:
library(ggplot2)
df <- as.data.frame(matrix(nrow = 7, ncol= 3,
data = c("ID1", "ID2", "ID3", "ID4", "ID5", "ID6", "ID7",
"north", "north", "north", "north", "south", "south", "south",
"A", "B", "B", "C", "A", "A", "C"),
byrow = FALSE))
colnames(df) <- c("ID", "region", "species")
p <- ggplot(df, aes(x = region, fill = species))
p + geom_bar()
I have a much larger table and R counts quite nicely the different species for every region. Now, I would like to show both, the original count value (preferably on the y-axis) and the percentage (as label) to compare proportions of species between regions.
I tried out many things using geom_text()
but I think the main difference to other questions (e.g. this one) is that
Any help is much appreciated!!
As @Gregor mentioned, summarize the data separately and then feed the data summary to ggplot. In the code below, we use dplyr
to create the summary on the fly:
library(dplyr)
ggplot(df %>% count(region, species) %>% # Group by region and species, then count number in each group
mutate(pct=n/sum(n), # Calculate percent within each region
ypos = cumsum(n) - 0.5*n), # Calculate label positions
aes(region, n, fill=species)) +
geom_bar(stat="identity") +
geom_text(aes(label=paste0(sprintf("%1.1f", pct*100),"%"), y=ypos))
Update: With dplyr
0.5 and later, you no longer need to provide a y-value to center the text within each bar. Instead you can use position_stack(vjust=0.5)
:
ggplot(df %>% count(region, species) %>% # Group by region and species, then count number in each group
mutate(pct=n/sum(n)), # Calculate percent within each region
aes(region, n, fill=species)) +
geom_bar(stat="identity") +
geom_text(aes(label=paste0(sprintf("%1.1f", pct*100),"%")),
position=position_stack(vjust=0.5))