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Apr 4, 2021
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Move "howto interpreting box plots" to boxplot docstring #19860

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19 changes: 0 additions & 19 deletions doc/faq/howto_faq.rst
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Expand Up @@ -494,25 +494,6 @@ you're all done issuing commands and you want to draw the figure now.
per script, and harmonized the behavior of interactive mode, across most
backends.

.. _howto-boxplot_violinplot:

Interpreting box plots and violin plots
---------------------------------------

Tukey's :doc:`box plots </gallery/statistics/boxplot_demo>` (Robert McGill,
John W. Tukey and Wayne A. Larsen: "The American Statistician" Vol. 32, No. 1,
Feb., 1978, pp. 12-16) are statistical plots that provide useful information
about the data distribution such as skewness. However, bar plots with error
bars are still the common standard in most scientific literature, and thus, the
interpretation of box plots can be challenging for the unfamiliar reader. The
figure below illustrates the different visual features of a box plot.

.. figure:: ../_static/boxplot_explanation.png

:doc:`Violin plots </gallery/statistics/violinplot>` are closely related to box
plots but add useful information such as the distribution of the sample data
(density trace). Violin plots were added in Matplotlib 1.4.

.. _how-to-threads:

Working with threads
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22 changes: 22 additions & 0 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -3714,6 +3714,28 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
meanprops : dict, default: None
The style of the mean.

Notes
-----
Box plots provide insight into distribution properties of the data.
However, they can be challenging to interpret for the unfamiliar
reader. The figure below illustrates the different visual features of
a box plot.
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@anntzer anntzer Apr 4, 2021 •
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consider also linking to the website version so that people displaying the docstring at their terminal have somewhere to click

or alternatively just replace the png by some ascii art:

       Q1-1.5IQR   Q1   median  Q3   Q3+1.5IQR
                    |-----:-----|
    .      |--------|     :     |--------|   .  .
                    |-----:-----|
 outlier            <----------->
                         IQR

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There's a link to wikipedia, which IMHO is sufficient.

Furthermore, this note only gives additional context. I assume that only a minority of people will try to learn from the docstring (It's rather used for looking up signature and specific parameters). I don't want to jump extra hoops here. You are welcome to do more yourself.


.. image:: /_static/boxplot_explanation.png
:alt: Illustration of box plot features
:scale: 50 %

The whiskers mark the range of the non-outlier data. The most common
definition of non-outlier is ``[Q1 - 1.5xIQR, Q3 + 1.5xIQR]``, which
is also the default in this function. Other whisker meanings can be
applied via the *whis* parameter.

See `Box plot <https://en.wikipedia.org/wiki/Box_plot>`_ on Wikipedia
for further information.

Violin plots (`~.Axes.violinplot`) add even more detail about the
statistical distribution by plotting the kernel density estimation
(KDE) as an estimation of the probability density function.
"""

# Missing arguments default to rcParams.
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