How to Plot the Relative Proportions of Two Groups Using a Fill Aesthetic in Ggplot2

How can I plot the relative proportions of two groups using a fill aesthetic in ggplot2?

This is an aweful hack, but it seems to do what you want...

ggplot(test, aes(test2)) + geom_bar(aes(y = ..count../rep(c(sum(..count..[1:6]), sum(..count..[7:12])), each=6), 
                                    group=test1, fill=test1) ,position="dodge") + 
                                      scale_y_continuous(name="proportion")

ggplot2 - Multi-group histogram with in-group proportions rather than frequency

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')

ggplot: relative frequencies of two groups

I usually do this by simply precalculating the values outside of ggplot2 and using stat = "identity":

df1 <- melt(ddply(df,.(gender),function(x){prop.table(table(x$outcome))}),id.vars = 1)

ggplot(df1, aes(x = variable,y = value)) +
    facet_wrap(~gender, nrow=2, ncol=1) +
    geom_bar(stat = "identity")

Unevenly spaced and overlapping lines for proportional stacked area graph on ggplot2 R

I fixed three things:

1. You want the x-scale to be treated categorically, so we need to factor(Timepoint). (And then the default scale will be fine, so we delete your manually specified limitsl)

2. When we use a discrete x-axis scale, we have to explicitly tell ggplot which dots we want to connect. We do this by adding the group = Taxa aesthetic.

3. The weird lines cutting through the middle of other polygons are because you don't have an observation for every taxa at every timepoint, so when the dots are connected they may cut through intermediate timepoints. Use tidyr::complete to fill in the missing observations with 0s.

library(tidyr)
S1_RA1 = S1_RA1 %>% ungroup %>%
  complete(Timepoint, Taxa, fill = list(n = 0, percentage = 0))

ggplot(S1_RA1, aes(x = factor(Timepoint), y = percentage, fill = Taxa, group = Taxa)) +
  geom_area(position = "fill", colour = "black", size = .5, alpha = .7) +
  scale_y_continuous(name="Relative Abundance", expand=c(0,0)) +
  scale_x_discrete(
    name="Timepoint (d)", expand=c(0,0) 
  ) + 
  scale_fill_manual(values = getPalette) + 
  theme(legend.position='bottom')

ggplot2 with fill and group

Is this what you had in mind?

library(reshape2)
library(ggplot2)
df <- aggregate(answer~which,testDat,
                function(x)c(yes=sum(x=="yes")/length(x),no=sum(x=="no")/length(x)))
df <- data.frame(which=df$which, df$answer)
gg <- melt(df,id=1, variable.name="Answer",value.name="Rel.Pct.")
ggplot(gg) + 
  geom_bar(aes(x=Answer, y=Rel.Pct., fill=Answer),position="dodge",stat="identity")+
  facet_wrap(~which)

Unfortunately, aggregating functions such as sum(...), min(...), max(...), range(...), etc. etc., when used in aesthetic mappings, do not respect the grouping implied by facets. So, while ..count.. is subsetted properly when used alone (in your numerator), sum(..count..) gives the total for the whole dataset. This is why (..count..)/sum(..count..) gives the fraction of the total, not the fraction of the group.

The only way around that, that I am aware of, is to create an axillary table as above.

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