ggplot2 - Multi-group histogram with in-group proportions rather than frequency
ggplot2, r
Solution
Wrong solution
You can use `stat_bin()` and `y=..density..` to get percentages in each group.
ggplot(df, alpha = 0.2,
aes(x = LetterGrade, group = ExperimentCohort, fill = ExperimentCohort))+
stat_bin(aes(y=..density..), position='dodge')
UPDATE - correct solution
As pointed out by @rpierce `y=..density..` will calculate density values for each group not the percentages (they are not the same).
To get the correct solution with percentages one way is to calculate them before plotting. For this used function `ddply()` from library `plyr`. In each `ExperimentCohort` calculated proportions using functions `prop.table()` and `table()` and saved them as `prop`. With `names()` and `table()` got back `LetterGrade`.
df.new<-ddply(df,.(ExperimentCohort),summarise,
prop=prop.table(table(LetterGrade)),
LetterGrade=names(table(LetterGrade)))
head(df.new)
ExperimentCohort prop LetterGrade
1 One 0.21739130 A
2 One 0.08695652 B
3 One 0.13043478 C
4 One 0.13043478 D
5 One 0.30434783 E
6 One 0.13043478 F
Now use this new data frame for plotting. As proportions are already calculated - provided them as `y` values and added `stat="identity"` inside the `geom_bar`.
ggplot(df.new,aes(LetterGrade,prop,fill=ExperimentCohort))+
geom_bar(stat="identity",position='dodge')
Problem
I have three cohorts of students identified by an `ExperimentCohort` factor. For each student, I have a `LetterGrade`, also a factor. I'd like to plot a histogram-like bar graph of `LetterGrade` for each `ExperimentCohort`. Using ``` ggplot(df, alpha = 0.2, aes(x = LetterGrade, group = ExperimentCohort, fill = ExperimentCohort)) + geom_bar(position = "dodge") ``` gets me very close, but the three `ExperimentCohorts` don't have the same number of students. To compare these on a more even field, I'd like the y-axis to be the in-cohort proportion of each letter-grade. So far, short of calculating this proportion and putting it in a separate dataframe before plotting, I have not been able to find a way to do this. Every solution to a similar question on SO and elsewhere involves `aes(y = ..count../sum(..count..))`, but sum(..count..) is executed across the whole dataframe rather than within each cohort. Anyone got a suggestion? Here's code to create an example dataframe: ``` df <- data.frame(ID = 1:60, LetterGrade = sample(c("A", "B", "C", "D", "E", "F"), 60, replace = T), ExperimentCohort = sample(c("One", "Two", "Three"), 60, replace = T)) ``` Thanks.