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DOC: Standardize example titles - part 2
Follow up to #28544. As there: Following recommendations from #28527, this improves example titles. Take this as an incremental improvement. I've changed what I saw t a glance when going through the examples once. Certainly, one could do further improvements, but that can be done in follow-ups. Co-authored-by: hannah <story645@gmail.com>
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‎galleries/examples/animation/pause_resume.py

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"""
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Pausing and resuming an animation
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Pause and resume an animation
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This example showcases:
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‎galleries/examples/axes_grid1/demo_axes_rgb.py

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"""
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Showing RGB channels using RGBAxes
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Show RGB channels using RGBAxes
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`~.axes_grid1.axes_rgb.RGBAxes` creates a layout of 4 Axes for displaying RGB
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channels: one large Axes for the RGB image and 3 smaller Axes for the R, G, B

‎galleries/examples/axes_grid1/demo_colorbar_with_inset_locator.py

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"""
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.. _demo-colorbar-with-inset-locator:
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Controlling the position and size of colorbars with Inset Axes
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Control the position and size of a colorbar with Inset Axes
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This example shows how to control the position, height, and width of colorbars
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using `~mpl_toolkits.axes_grid1.inset_locator.inset_axes`.

‎galleries/examples/axes_grid1/demo_imagegrid_aspect.py

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"""
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Setting a fixed aspect on ImageGrid cells
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ImageGrid cells with a fixed aspect ratio
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"""
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‎galleries/examples/color/custom_cmap.py

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"""
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Creating a colormap from a list of colors
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Create a colormap from a list of colors
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For more detail on creating and manipulating colormaps see
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:ref:`colormap-manipulation`.

‎galleries/examples/images_contours_and_fields/image_annotated_heatmap.py

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"""
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Creating annotated heatmaps
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Annotated heatmap
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It is often desirable to show data which depends on two independent
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variables as a color coded image plot. This is often referred to as a

‎galleries/examples/lines_bars_and_markers/bar_colors.py

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"""
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Bar color demo
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Bar chart with individual bar colors
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This is an example showing how to control bar color and legend entries
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using the *color* and *label* parameters of `~matplotlib.pyplot.bar`.

‎galleries/examples/lines_bars_and_markers/fill_between_alpha.py

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"""
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Fill Between with transparency
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``fill_between`` with transparency
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The `~matplotlib.axes.Axes.fill_between` function generates a shaded
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region between a min and max boundary that is useful for illustrating ranges.

‎galleries/examples/lines_bars_and_markers/fill_between_demo.py

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"""
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Filling the area between lines
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Fill the area between two lines
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This example shows how to use `~.axes.Axes.fill_between` to color the area
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between two lines.

‎galleries/examples/lines_bars_and_markers/fill_betweenx_demo.py

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"""
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Fill Betweenx Demo
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Fill the area between two vertical lines
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Using `~.Axes.fill_betweenx` to color along the horizontal direction between
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two curves.

‎galleries/examples/lines_bars_and_markers/line_demo_dash_control.py

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"""
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Customizing dashed line styles
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Dashed line style configuration
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The dashing of a line is controlled via a dash sequence. It can be modified
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using `.Line2D.set_dashes`.

‎galleries/examples/lines_bars_and_markers/scatter_masked.py

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"""
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Scatter with masked values
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Scatter plot with masked values
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Mask some data points and add a line demarking
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masked regions.

‎galleries/examples/lines_bars_and_markers/scatter_with_legend.py

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"""
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Scatter plots with a legend
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Scatter plot with a legend
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To create a scatter plot with a legend one may use a loop and create one
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`~.Axes.scatter` plot per item to appear in the legend and set the ``label``

‎galleries/examples/lines_bars_and_markers/timeline.py

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Creating a timeline with lines, dates, and text
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Timeline with lines, dates, and text
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How to create a simple timeline using Matplotlib release dates.
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‎galleries/examples/misc/bbox_intersect.py

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Changing colors of lines intersecting a box
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Identify whether artists intersect
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The lines intersecting the rectangle are colored in red, while the others
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are left as blue lines. This example showcases the `.intersects_bbox` function.

‎galleries/examples/misc/demo_ribbon_box.py

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"""
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Ribbon Box
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Ribbon box
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"""

‎galleries/examples/misc/fig_x.py

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"""
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Adding lines to figures
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Add lines directly to a figure
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Adding lines to a figure without any Axes.
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You can add artists such as a `.Line2D` directly to a figure. This is
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typically useful for visual structuring.
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.. redirect-from:: /gallery/pyplots/fig_x
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fig, axs = plt.subplots(2, 2, gridspec_kw={'hspace': 0.4, 'wspace': 0.4})
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fig.add_artist(lines.Line2D([0, 1], [0.47, 0.47], linewidth=3))
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fig.add_artist(lines.Line2D([0.5, 0.5], [1, 0], linewidth=3))
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plt.show()
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# %%

‎galleries/examples/misc/fill_spiral.py

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"""
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Fill spiral
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"""

‎galleries/examples/pie_and_polar_charts/pie_and_donut_labels.py

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"""
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Welcome to the Matplotlib bakery. We will create a pie and a donut
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chart through the `pie method <matplotlib.axes.Axes.pie>` and

‎galleries/examples/shapes_and_collections/line_collection.py

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Matplotlib can efficiently draw multiple lines at once using a `~.LineCollection`.
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"""

‎galleries/examples/statistics/errorbars_and_boxes.py

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Create boxes from error bars using PatchCollection
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In this example, we snazz up a pretty standard error bar plot by adding
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a rectangle patch defined by the limits of the bars in both the x- and

‎galleries/examples/statistics/histogram_cumulative.py

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This example shows how to plot the empirical cumulative distribution function
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(ECDF) of a sample. We also show the theoretical CDF.

‎galleries/examples/statistics/multiple_histograms_side_by_side.py

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Multiple histograms side by side
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This example plots horizontal histograms of different samples along
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a categorical x-axis. Additionally, the histograms are plotted to

‎galleries/examples/subplots_axes_and_figures/auto_subplots_adjust.py

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Programmatically control subplot adjustment
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.. note::
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‎galleries/examples/subplots_axes_and_figures/axhspan_demo.py

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Draw regions that span an Axes
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`~.Axes.axhspan` and `~.Axes.axvspan` draw rectangles that span the Axes in either
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the horizontal or vertical direction and are bounded in the other direction. They are

‎galleries/examples/subplots_axes_and_figures/demo_constrained_layout.py

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*Constrained layout* attempts to resize subplots in
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a figure so that there are no overlaps between Axes objects and labels
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`~.Figure.tight_layout` attempts to resize subplots in a figure so that there
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are no overlaps between Axes objects and labels on the Axes.
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To create plots that share a common axis (visually) you can set the hspace
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between the subplots to zero. Passing sharex=True when creating the subplots
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Combining two subplots using subplots and GridSpec
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Combine two subplots using subplots and GridSpec
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Sometimes we want to combine two subplots in an Axes layout created with
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`~.Figure.subplots`. We can get the `~.gridspec.GridSpec` from the Axes
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`.GridSpec` is a flexible way to layout
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subplot grids. Here is an example with a 3x3 grid, and
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`matplotlib.pyplot` uses the concept of a *current figure* and *current Axes*.
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Figures are identified via a figure number that is passed to `~.pyplot.figure`.
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"""
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Create multiple subplots using ``plt.subplots``
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`.pyplot.subplots` creates a figure and a grid of subplots with a single call,
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while providing reasonable control over how the individual plots are created.
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"""
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"""
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Use of the engineering Formatter.
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"""
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