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DOC examples/statistics is fully SG
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‎doc/users/prev_whats_new/whats_new_1.4.rst‎

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Lastly, each artist (e.g., the box, outliers, cap, notches) can now be
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toggled on or off and their styles can be passed in through individual
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kwargs. See the examples:
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:ref:`statistics-boxplot_demo` and
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:ref:`statistics-bxp_demo`
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:ref:`statistics-plot_boxplot` and
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:ref:`statistics-plot_bxp`
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Added a bool kwarg, :code:`manage_xticks`, which if False disables the management
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of the ticks and limits on the x-axis by :func:`~matplotlib.axes.Axes.bxp`.

‎doc/users/screenshots.rst‎

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The :func:`~matplotlib.pyplot.hist` command automatically generates
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histograms and returns the bin counts or probabilities:
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.. plot:: mpl_examples/statistics/histogram_demo_features.py
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.. plot:: auto_examples/statistics/plot_histogram_features.py
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.. _screenshots_path_demo:

‎examples/README‎

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Matplotlib examples
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===================
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There are a variety of ways to use Matplotlib, and most of them are
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illustrated in the examples in this directory.
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Probably the most common way people use Matplotlib is with the
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procedural interface, which follows the MATLAB/IDL/Mathematica approach
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of using simple procedures like "plot" or "title" to modify the current
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figure. These examples are included in the "pylab_examples" directory.
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If you want to write more robust scripts, e.g., for production use or in
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a web application server, you will probably want to use the Matplotlib
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API for full control. These examples are found in the "api" directory.
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Below is a brief description of the different directories found here:
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* animation - Dynamic plots, see the documentation at
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http://matplotlib.org/api/animation_api.html
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* api - working with the Matplotlib API directly.
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* axes_grid1 - Examples related to the axes_grid1 toolkit.
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* axisartist - Examples related to the axisartist toolkit.
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* event_handling - How to interact with your figure, mouse presses,
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key presses, object picking, etc.
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* misc - Miscellaneous examples. Some demos for loading and working
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with record arrays.
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* mplot3d - 3D examples.
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* pylab_examples - The interface to Matplotlib similar to MATLAB.
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* tests - Tests used by Matplotlib developers to check functionality.
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(These tests are still sometimes useful, but mostly developers should
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use the pytest tests which perform automatic image comparison.)
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* units - Working with unit data and custom types in Matplotlib.
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* user_interfaces - Using Matplotlib in a GUI application, e.g.,
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Tkinter, wxPython, PyGObject, PyQt widgets.
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* widgets - Examples using interactive widgets.

‎examples/README.txt‎

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Matplotlib examples
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===================
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.. _gallery:
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There are a variety of ways to use Matplotlib, and most of them are
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illustrated in the examples in this directory.
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Gallery
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=======
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Probably the most common way people use Matplotlib is with the
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procedural interface, which follows the MATLAB/IDL/Mathematica approach
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of using simple procedures like "plot" or "title" to modify the current
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figure. These examples are included in the "pylab_examples" directory.
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If you want to write more robust scripts, e.g., for production use or in
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a web application server, you will probably want to use the Matplotlib
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API for full control. These examples are found in the "api" directory.
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Below is a brief description of the different directories found here:
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Click on any image to see full size image and source code.
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* animation - Dynamic plots, see the documentation at
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http://matplotlib.org/api/animation_api.html
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* api - working with the Matplotlib API directly.
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* axes_grid1 - Examples related to the axes_grid1 toolkit.
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* axisartist - Examples related to the axisartist toolkit.
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* event_handling - How to interact with your figure, mouse presses,
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key presses, object picking, etc.
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* misc - Miscellaneous examples. Some demos for loading and working
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with record arrays.
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* mplot3d - 3D examples.
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* pylab_examples - The interface to Matplotlib similar to MATLAB.
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* tests - Tests used by Matplotlib developers to check functionality.
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(These tests are still sometimes useful, but mostly developers should
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use the pytest tests which perform automatic image comparison.)
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* units - Working with unit data and custom types in Matplotlib.
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* user_interfaces - Using Matplotlib in a GUI application, e.g.,
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Tkinter, wxPython, PyGObject, PyQt widgets.
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* widgets - Examples using interactive widgets.
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.. contents::

‎examples/statistics/README.txt‎

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.. _statistics_examples:
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Statistics
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==========

examples/statistics/boxplot_demo.py renamed to examples/statistics/plot_boxplot.py

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examples/statistics/boxplot_color_demo.py renamed to examples/statistics/plot_boxplot_color.py

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examples/statistics/boxplot_vs_violin_demo.py renamed to examples/statistics/plot_boxplot_vs_violin.py

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examples/statistics/bxp_demo.py renamed to examples/statistics/plot_bxp.py

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examples/statistics/customized_violin_demo.py renamed to examples/statistics/plot_customized_violin.py

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