matplotlib-devel Mailing List for matplotlib

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 <sf...@on...> wrote:
>
> On 2014年2月15日, 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
tca...@uc...
jfi.uchicago.edu/~tcaswell
o: 773.702.7204

On 2014年2月15日, 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