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Commit 5e9e20b

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Use plt.subplots() in usage guide
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‎tutorials/introductory/usage.py

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# Matplotlib graphs your data on `~.figure.Figure`\s (i.e., windows, Jupyter
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# widgets, etc.), each of which can contain one or more `~.axes.Axes` (i.e., an
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# area where points can be specified in terms of x-y coordinates (or theta-r
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# in a polar plot, or x-y-z in a 3D plot, etc.). In the following example, we
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# create a figure using the `.pyplot.figure` function, an axes on that figure
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# using the `.Figure.add_subplot` method, and graph some data on that axes
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# using the `.Axes.plot` method:
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# in a polar plot, or x-y-z in a 3D plot, etc.). The most simple way of
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# creating a figure with an axes is using `.pyplot.subplots`. We can then use
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# `.Axes.plot` to draw some data on the axes:
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fig = plt.figure() # Create a figure.
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ax = fig.add_subplot() # Add an axes to the figure.
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fig, ax = plt.subplots() # Create a figure containing a single axes.
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ax.plot([1, 2, 3, 4], [1, 4, 2, 3]) # Plot some data on the axes.
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###############################################################################
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# 'special' artists (titles, figure legends, etc), and the **canvas**.
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# (Don't worry too much about the canvas, it is crucial as it is the
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# object that actually does the drawing to get you your plot, but as the
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# user it is more-or-less invisible to you). A figure can have any
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# number of :class:`~matplotlib.axes.Axes`, but to be useful should have
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# user it is more-or-less invisible to you). A figure can contain any
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# number of :class:`~matplotlib.axes.Axes`, but will typically have
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# at least one.
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#
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# The easiest way to create a new figure is with pyplot:
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fig = plt.figure() # an empty figure with no axes
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fig.suptitle('No axes on this figure') # Add a title so we know which it is
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fig = plt.figure() # an empty figure with no Axes
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fig, ax = plt.subplots() # a figure with a single Axes
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fig, axs = plt.subplots(2, 2) # a figure with a 2x2 grid of Axes
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fig, ax_lst = plt.subplots(2, 2) # a figure with a 2x2 grid of Axes
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# It's convenient to create the axes together with the figure, but you can
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# also add axes later on, allowing for more complex axes layouts.
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###############################################################################
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# :class:`~matplotlib.axes.Axes`
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x = np.linspace(0, 2, 100)
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# Note that even in the OO-style, we use `.pyplot.figure` to create the figure.
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fig = plt.figure() # Create a figure.
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ax = fig.add_subplot() # Add an axes to the figure.
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fig, ax = plt.subplots() # Create a figure and an axes.
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ax.plot(x, x, label='linear') # Plot some data on the axes.
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ax.plot(x, x**2, label='quadratic') # Plot more data on the axes...
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ax.plot(x, x**3, label='cubic') # ... and some more.

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