As a side note, adding jitter has been discussed before
(https://github.com/matplotlib/matplotlib/issues/2750) in a slightly
different context and the consensus was to _not_ add it to mpl (as it
is a non-deterministic data transformation).

Tom

On Sat, Feb 15, 2014 at 10:45 PM, Yaroslav Halchenko <s...@onerussian.com> 
wrote:
>
> On Sat, 15 Feb 2014, Paul Hobson wrote:
>>    Those figures look great. Seaborn has some similar functionality (scroll
>>    down a bit):
>>    
>> [1]http://nbviewer.ipython.org/github/mwaskom/seaborn/blob/master/examples/plotting_distributions.ipynb#Comparing-distributions:-boxplot-and-violinplot
>
> right -- seaborn looks really nice and I am yet to take advantage of it.
>
> BUT that is why we are talking here, at matplotlib list:  seaborn (and
> few others) while aiming to provide high level convenience, specific to
> e.g. using pandas as the core datastructures, add improvements which
> could easily go into stock matplotlib and thus benefit all of the users.
> That is why I thought that improving boxplot itself could be of
> more generic benefit, while allowing all the dependent projects take
> advantage of it without requiring unnecessary fragmentation (e.g. "use
> seaborn for paired plots", which could easily go straight into stock
> boxplot operating on arrays).
>
> Even violin plots could probably could be done in matplotlib with
> some basic density estimator (with parameter for a custom one) as an
> option within boxplot function itself.
>
>>    The main point of the most recent overhaul of boxplots was to allow users
>>    to just what you describe. The methods plt.boxplot and ax.boxplot now do
>>    very little on their own. Input data are passed to
>>    matplotlib.cbook.boxplot_stats, that function returns a list of
>>    dictionaries of statistics, and then ax.bxp actually does the drawing. All
>>    of this is to say that you can write your own function to modify
>>    boxplot_stats' output or generate independently the list of dictionaries
>>    expected by ax.bxp.
>>    The keys of those dictionaries can include:
>>     - label  -> tick label for the boxplot
>>     - mean -> mean value (can plot as a line or point)
>>     - median -> 50th percentile
>>     - q1 -> first quartile (25th pctl)
>>     - q3 -> third quartile (75 (pctl)
>>     - cilo -> lower notch around the median
>>     - ciho -> upper notch around the median
>>     - whislo -> end of the lower whisker
>>     - whishi -> end of the upper whisker
>>     - fliers -> outliers
>>    Basically, you can set the appropriate values to whatever you want to draw
>>    boxplots however you wish (like open/close diagrams for pandas).
>>    Also, the `whis` kwarg accepted by boxplot and cbook.boxplot_stats can
>>    either be a float (1.5 by default), a list of integer percentiles (like 5,
>>    95), or the strings 'range', 'limits', or 'min/max', all of which will
>>    extend the whiskers to over all of the data.
>>    Since you're running off of master, you should access to this new
>>    functionality.
>
> ;-) usually I run off the releases and even more often from releases in
> Debian stable.  But yes -- I have the master and this new functionality
> looks neat -- thanks again.  But those few enhancements, such as
>
> - plot actual datapoints with the jitter
> - plot pairing lines across boxplots
>
> seems to be not there and I would consider them worthwhile enhancement
>
>>    Feel free to hit me up with any other questions!
>
> sorry that I have hit with not really a question above ;-)
> --
> Yaroslav O. Halchenko, Ph.D.
> http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org
> Senior Research Associate,     Psychological and Brain Sciences Dept.
> Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
> Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
> WWW:   http://www.linkedin.com/in/yarik
>
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-- 
Thomas A Caswell
PhD Candidate University of Chicago
Nagel and Gardel labs
tcasw...@uchicago.edu
jfi.uchicago.edu/~tcaswell
o: 773.702.7204

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