To quickly visualize the differences between measurements, I want to use gnuplot to draw two (later multiple) boxplots combined in a single plot.
Basically I want to visualize the Five-number-summary (Min. 1st Qu. Median Mean 3rd Qu. Max.) of each measurement.
Each column in my 'datafile' represents samples of a measurement.
My data is in this form:
A B C D
1.008 1.008 . .
0.909 0.909 . .
0.975 0.975
2.647 2.647
6.530 1.901
1.819 0.909
1.819 0.909
2.695 0.909
0.529 0.529
0.964 0.964
2.728 0.909
1.819 0.909
4.133 1.108
11.275 6.133
5.920 5.920
. .
and I would like it to look like the boxplot demo.
However I cannot get the demo to work since they seem to use a third column to slide one boxplot to the right, but I do not really understand how that works.
For clarification, in R I would do something like this:
par(mfrow=c(1,3))
b1 <- boxplot(datafile$A)
b2 <- boxplot(datafile$B)
b3 <- boxplot(datafile$C)
I'm also wondering how I can plot the boxplots on the same scale. I'm worried that the few really high values might stretch the max. whiskers of the boxplot so much that the box itself becomes too tiny for me to see differences between the medians of the two boxes.
Edit:
The suggested solution was ok until I tried to also plot the rest of my data. If I plot my data the plots become so crowded that it's impossible to see something.
Below is an example with only the first 1000 entries of the rest of my data.
How can I include the outliers into the boxes? (I do not want to discard them.)