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Merge pull request #8391 from phobson/update-mep28
DOC: Update MEP 28
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doc/devel/MEP/MEP28.rst

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=============================================
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MEP 28: Remove Complexity from Axes.boxplot
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MEP28: Remove Complexity from Axes.boxplot
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=============================================
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.. contents::
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:local:
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Status
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======
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..
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.. MEPs go through a number of phases in their lifetime:
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**Discussion**
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..
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.. - **Progress**: Consensus was reached on the mailing list and
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.. implementation work has begun.
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..
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.. - **Completed**: The implementation has been merged into master.
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..
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.. - **Superseded**: This MEP has been abandoned in favor of another
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.. approach.
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Branches and Pull requests
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==========================
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Adding pre- & post-processing options to ``cbook.boxplot_stats``: https://github.com/phobson/matplotlib/tree/boxplot-stat-transforms
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Exposing ``cbook.boxplot_stats`` through ``Axes.boxplot`` kwargs: None
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Remove redundant statistical kwargs in ``Axes.boxplot``: None
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Remove redundant style options in ``Axes.boxplot``: None
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Remaining items that arise through discussion: None
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The following lists any open PRs or branches related to this MEP:
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#. Deprecate redundant statistical kwargs in ``Axes.boxplot``: https://github.com/phobson/matplotlib/tree/MEP28-initial-deprecations
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#. Deprecate redundant style options in ``Axes.boxplot``: https://github.com/phobson/matplotlib/tree/MEP28-initial-deprecations
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#. Deprecate passings 2D numpy arrays as input: None
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#. Add pre- & post-processing options to ``cbook.boxplot_stats``: https://github.com/phobson/matplotlib/tree/boxplot-stat-transforms
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#. Exposing ``cbook.boxplot_stats`` through ``Axes.boxplot`` kwargs: None
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#. Remove redundant statistical kwargs in ``Axes.boxplot``: None
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#. Remove redundant style options in ``Axes.boxplot``: None
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#. Remaining items that arise through discussion: None
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Abstract
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========
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ax.set_yscale('log')
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data = np.random.lognormal(-1.75, 2.75, size=37)
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stats = cbook.boxplot_stats(data, labels=['arimetic'])
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stats = cbook.boxplot_stats(data, labels=['arithmetic'])
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logstats = cbook.boxplot_stats(np.log(data), labels=['log-transformed'])
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for lsdict in logstats:
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An accelerated timeline could look like the following:
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#. v2.0.1 add transforms to ``cbook.boxplots_stats``, expose in ``Axes.boxplot``
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#. v2.1.0 deprecate ``usermedians``, ``conf_intervals``, ``sym`` parameters
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#. v2.2.0 make deprecations noisier
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#. v2.3.0 remove ``usermedians``, ``conf_intervals``, ``sym`` parameters
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#. v2.3.0 deprecate ``notch`` in favor of ``shownotches`` to be consistent with other parameters and ``Axes.bxp``
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#. v2.4.0 remove ``notch`` parameter, move all style and artist toggling logic to ``Axes.bxp``. ``Axes.boxplot`` is little more than a broker between ``Axes.bxp`` and ``cbook.boxplots_stats``
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#. v2.1.0 Initial Deprecations , and using 2D numpy arrays as input
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a. Using 2D numpy arrays as input. The semantics around 2D arrays are generally confusing.
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b. ``usermedians``, ``conf_intervals``, ``sym`` parameters
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#. v2.2.0
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a. remove ``usermedians``, ``conf_intervals``, ``sym`` parameters
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b. deprecate ``notch`` in favor of ``shownotches`` to be consistent with
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other parameters and ``Axes.bxp``
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#. v2.3.0
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a. remove ``notch`` parameter
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b. move all style and artist toggling logic to ``Axes.bxp`` such ``Axes.boxplot``
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is little more than a broker between ``Axes.bxp`` and ``cbook.boxplots_stats``
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Anticipated Impacts to Users

lib/matplotlib/axes/_axes.py

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whis = rcParams['boxplot.whiskers']
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if bootstrap is None:
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bootstrap = rcParams['boxplot.bootstrap']
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bxpstats = cbook.boxplot_stats(x, whis=whis, bootstrap=bootstrap,
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labels=labels, autorange=autorange)
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if notch is None:

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