Draw mean and outlier points for box plots using ggplot2 - r

Question

I am trying to plot the outliers and mean point for the box plots in below using the data available here. The dataset has 3 different factors and 1 value column for 3600 rows.
While I run the below the code it shows the mean point but doesn't draw the outliers properly
ggplot(df, aes(x=Representations, y=Values, fill=Methods)) +
geom_boxplot() +
facet_wrap(~Metrics) +
stat_summary(fun.y=mean, colour="black", geom="point", position=position_dodge(width=0.75)) +
geom_point() +
theme_bw()
Again, while I am modify the code like in below the mean points disappear !!
ggplot(df, aes(x=Representations, y=Values, colour=Methods)) +
geom_boxplot() +
facet_wrap(~Metrics) +
stat_summary(fun.y=mean, colour="black", geom="point", position=position_dodge(width=0.75)) +
geom_point() +
theme_bw()
In both of the cases I am getting the message: "ymax not defined: adjusting position using y instead" 3 times.
Any kind suggestions how to fix it? I would like to draw the mean points within individual box plots and show outliers in the same colour as the plots.
EDIT:
The original data set does not have any outliers and that was reason for my confusion. Thanks to MrFlick's answer with randomly generated data which clarifies it properly.

Answer 1

Rather than downloading the data, I just made a random sample.
set.seed(18)
gg <- expand.grid (
Methods=c("BC","FD","FDFND","NC"),
Metrics=c("DM","DTI","LB"),
Representations=c("CHG","QR","HQR")
)
df <- data.frame(
gg,
Values=rnorm(nrow(gg)*50)
)
Then you should be able to create the plot you want with
library(ggplot2)
ggplot(df, aes(x=Representations, y=Values, fill=Methods)) +
geom_boxplot() +
stat_summary(fun.y="mean", geom="point",
position=position_dodge(width=0.75), color="white") +
facet_wrap(~Metrics)
which gave me
I was using ggplot2 version 0.9.3.1