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categorical variable example
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‎doc/api/pyplot_summary.rst

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Plotting commands summary
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=========================
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Below we describe several common approaches to plotting with Matplotlib.
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.. contents::
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The Pyplot API
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--------------
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The :mod:`matplotlib.pyplot` module contains functions that allow you to generate
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many kinds of plots quickly. For examples that showcase the use
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of the :mod:`matplotlib.pyplot` module, see the
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:ref:`sphx_glr_tutorials_01_introductory_pyplot.py`
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or the :ref:`pyplots_examples`.
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or the :ref:`pyplots_examples`. We also recommend that you look into
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the object-oriented approach to plotting, described below.
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.. currentmodule:: matplotlib.pyplot
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.. autofunction:: plotting
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The Object-Oriented API
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-----------------------
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Most of these functions also exist as methods in the
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:class:`matplotlib.axes.Axes` class. You can use them with the
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so-called "Object Oriented" approach to Matplotlib.
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and customization of your plots. For some examples of the OO approach
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to Matplotlib, see the :ref:`api_examples` examples.
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The Pyplot API
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--------------
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Colors in Matplotlib
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--------------------
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.. currentmodule:: matplotlib.pyplot
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There are many colormaps you can use to map data onto color values.
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Below we list several ways in which color can be utilized in Matplotlib.
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.. autofunction:: plotting
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For a more in-depth look at colormaps, see the
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:ref:`sphx_glr_tutorials_colors_colormaps.py` tutorial.
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.. autofunction:: colormaps

‎examples/lines_bars_and_markers/categorical_variables.py

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"""
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==============================
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Plotting categorical variables
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==============================
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How to use categorical variables in matplotlib.
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Many times you want to create a plot that uses categorical variables
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in Matplotlib. For example, your data may naturally fall into
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several "bins" and you're interested in summarizing the data per
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bin. Matplotlib allows you to pass categorical variables directly to
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many plotting functions.
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"""
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import matplotlib.pyplot as plt
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names = ['group_a', 'group_b', 'group_c']
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values = [1, 10, 100]
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fig, axs = plt.subplots(1, 3, figsize=(9, 3))
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axs[0].bar(names, values)
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axs[1].scatter(names, values)
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axs[2].plot(names, values)
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fig.suptitle('Categorical Plotting')
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plt.show()

‎tutorials/01_introductory/pyplot.py

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plt.ylabel('entry b')
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plt.show()
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###############################################################################
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# .. _plotting-with-categorical-vars:
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#
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# Plotting with categorical variables
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# ===================================
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#
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# It is also possible to create a plot using categorical variables
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# Matplotlib allows you to pass categorical variables directly to
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# many plotting functions. For example:
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names = ['group_a', 'group_b', 'group_c']
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values = [1, 10, 100]
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fig, axs = plt.subplots(1, 3, figsize=(9, 3))
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axs[0].bar(names, values)
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axs[1].scatter(names, values)
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axs[2].plot(names, values)
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fig.suptitle('Categorical Plotting')
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plt.show()
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###############################################################################
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# .. _controlling-line-properties:
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#

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