Matplotlib gurus:

I took at stab at the git work flow and incorporated my personal

modifications to the boxplot function. Github's diff can be found

here:

https://github.com/phobson/matplotlib/compare/master...manual_boxplots

In summary, if your data is MxN, you can manually specify medians and

the confidence intervals around the medians using Nx1 and Nx2 arrays,

respectively. Alternatively, you can use lists or tuples and use Nones

if you want to specify those values only for some columns in your MxN

data set. In other words, with an Mx5 data array, you can specify

conf_intervals=[(ci1a,ci2a), (ci1b,ci2b), (ci1c,ci2c), None,

(ci1e,ci2e)]. Within the conf_intervals "array", the CIs can be listed

in any order as I use np.max() and np.min() to pull the upper and

lower values, respectively.

The motivation behind this is that sometimes I need the confidence

levels to be different than 95%, and also that I compute those

confidence intervals with a bootstrapping routine that is more robust

than mpl-compatible one I submitted some time ago.

I hope y'all find this to be a useful contribution. I'm an avid

matplotlib user. It really is a wonderful tool.

Cheers,

paul h