diff --git a/doc/release/next_whats_new/3d_scales.rst b/doc/release/next_whats_new/3d_scales.rst
deleted file mode 100644
index e92b8e0abb61..000000000000
--- a/doc/release/next_whats_new/3d_scales.rst
+++ /dev/null
@@ -1,35 +0,0 @@
-Non-linear scales on 3D axes
-----------------------------
-
-Resolving a long-standing issue, 3D axes now support non-linear axis scales
-such as 'log', 'symlog', 'logit', 'asinh', and custom 'function' scales, just
-like 2D axes. Use `~.Axes3D.set_xscale`, `~.Axes3D.set_yscale`, and
-`~.Axes3D.set_zscale` to set the scale for each axis independently.
-
-.. plot::
-    :include-source: true
-    :alt: A 3D plot with a linear x-axis, logarithmic y-axis, and symlog z-axis.
-
-    import matplotlib.pyplot as plt
-    import numpy as np
-
-    # A sine chirp with increasing frequency and amplitude
-    x = np.linspace(0, 1, 400)  # time
-    y = 10 ** (2 * x)  # frequency, growing exponentially from 1 to 100 Hz
-    phase = 2 * np.pi * (10 ** (2 * x) - 1) / (2 * np.log(10))
-    z = np.sin(phase) * x ** 2 * 10  # amplitude, growing quadratically
-
-    fig = plt.figure()
-    ax = fig.add_subplot(projection='3d')
-    ax.plot(x, y, z)
-
-    ax.set_xlabel('Time (linear)')
-    ax.set_ylabel('Frequency, Hz (log)')
-    ax.set_zlabel('Amplitude (symlog)')
-
-    ax.set_yscale('log')
-    ax.set_zscale('symlog')
-
-    plt.show()
-
-See `matplotlib.scale` for details on all available scales and their parameters.
diff --git a/doc/release/next_whats_new/3d_speedups.rst b/doc/release/next_whats_new/3d_speedups.rst
deleted file mode 100644
index 70e80bfbdccb..000000000000
--- a/doc/release/next_whats_new/3d_speedups.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-3D performance improvements
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-Draw time for 3D plots has been improved, especially for surface and wireframe
-plots. Users should see up to a 10x speedup in some cases. This should make
-interacting with 3D plots much more responsive.
diff --git a/doc/release/next_whats_new/axis_inversion.rst b/doc/release/next_whats_new/axis_inversion.rst
deleted file mode 100644
index 8d0e161b9ab2..000000000000
--- a/doc/release/next_whats_new/axis_inversion.rst
+++ /dev/null
@@ -1,9 +0,0 @@
-Standard getters/setters for axis inversion state
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-Whether an axis is inverted can now be queried and set using the `.axes.Axes`
-getters `~.Axes.get_xinverted`/`~.Axes.get_yinverted` and setters
-`~.Axes.set_xinverted`/`~.Axes.set_yinverted`.
-
-The previously existing methods (`.Axes.xaxis_inverted`, `.Axes.invert_xaxis`)
-are now discouraged (but not deprecated) due to their non-standard naming and
-behavior.
diff --git a/doc/release/next_whats_new/bar_label_padding_update.rst b/doc/release/next_whats_new/bar_label_padding_update.rst
deleted file mode 100644
index 7a2ef73c41ca..000000000000
--- a/doc/release/next_whats_new/bar_label_padding_update.rst
+++ /dev/null
@@ -1,4 +0,0 @@
-``bar_label`` supports individual padding per label
----------------------------------------------------
-``bar_label`` will now accept both a float value or an array-like for
-padding. The array-like defines the padding for each label individually.
diff --git a/doc/release/next_whats_new/barcontainer_properties.rst b/doc/release/next_whats_new/barcontainer_properties.rst
deleted file mode 100644
index 0efe4ee00e4f..000000000000
--- a/doc/release/next_whats_new/barcontainer_properties.rst
+++ /dev/null
@@ -1,7 +0,0 @@
-``BarContainer`` properties
----------------------------
-`.BarContainer` gained new properties to easily access coordinates of the bars:
-
-- `~.BarContainer.bottoms`
-- `~.BarContainer.tops`
-- `~.BarContainer.position_centers`
diff --git a/doc/release/next_whats_new/box_arrow_size_controls.rst b/doc/release/next_whats_new/box_arrow_size_controls.rst
deleted file mode 100644
index 6fb2b69e49fd..000000000000
--- a/doc/release/next_whats_new/box_arrow_size_controls.rst
+++ /dev/null
@@ -1,37 +0,0 @@
-Arrow-style sub-classes of ``BoxStyle`` support arrow head resizing
--------------------------------------------------------------------
-
-The new *head_width* and *head_angle* parameters to
-`.BoxStyle.LArrow`, `.BoxStyle.RArrow` and `.BoxStyle.DArrow` allow for adjustment
-of the size and aspect ratio of the arrow heads used.
-
-To give a consistent appearance across all parameter values, the
-default head position (where the head starts relative to text) is
-slightly changed compared to the previous hard-coded position.
-
-By using negative angles (or corresponding reflex angles) for *head_angle*, arrows
-with 'backwards' heads may be created.
-
-.. plot::
-    :include-source: true
-    :alt:
-        Six arrow-shaped text boxes.  The arrows on the left have the shaft on
-        their left; the arrows on the right have the shaft on the right; the
-        arrows in the middle have shafts on both sides.
-
-    import matplotlib.pyplot as plt
-
-    plt.text(0.2, 0.8, "LArrow", ha='center', size=16,
-             bbox=dict(boxstyle="larrow, pad=0.3, head_angle=150"))
-    plt.text(0.2, 0.2, "LArrow", ha='center', size=16,
-             bbox=dict(boxstyle="larrow, pad=0.3, head_width=0.5"))
-    plt.text(0.5, 0.8, "DArrow", ha='center', size=16,
-             bbox=dict(boxstyle="darrow, pad=0.3, head_width=3"))
-    plt.text(0.5, 0.2, "DArrow", ha='center', size=16,
-             bbox=dict(boxstyle="darrow, pad=0.3, head_width=1, head_angle=60"))
-    plt.text(0.8, 0.8, "RArrow", ha='center', size=16,
-             bbox=dict(boxstyle="rarrow, pad=0.3, head_angle=30"))
-    plt.text(0.8, 0.2, "RArrow", ha='center', size=16,
-             bbox=dict(boxstyle="rarrow, pad=0.3, head_width=2, head_angle=-90"))
-
-    plt.show()
diff --git a/doc/release/next_whats_new/broken_barh_align.rst b/doc/release/next_whats_new/broken_barh_align.rst
deleted file mode 100644
index 5108ac5b0e9a..000000000000
--- a/doc/release/next_whats_new/broken_barh_align.rst
+++ /dev/null
@@ -1,4 +0,0 @@
-``broken_barh()`` vertical alignment though ``align`` parameter
----------------------------------------------------------------
-`~.Axes.broken_barh` now supports vertical alignment of the bars through the
-``align`` parameter.
diff --git a/doc/release/next_whats_new/callback_registry_disconnect_func.rst b/doc/release/next_whats_new/callback_registry_disconnect_func.rst
deleted file mode 100644
index 05825fe7e774..000000000000
--- a/doc/release/next_whats_new/callback_registry_disconnect_func.rst
+++ /dev/null
@@ -1,19 +0,0 @@
-``CallbackRegistry.disconnect`` allows directly callbacks by function
--------------------------------------------------------------------------
-
-`.CallbackRegistry` now allows directly passing a function and optionally signal to
-`~.CallbackRegistry.disconnect` instead of needing to track the callback ID
-returned by `~.CallbackRegistry.connect`.
-
-.. code-block:: python
-
-    from matplotlib.cbook import CallbackRegistry
-
-    def my_callback(event):
-        print(event)
-
-    callbacks = CallbackRegistry()
-    callbacks.connect('my_signal', my_callback)
-
-    # Disconnect by function reference instead of callback ID
-    callbacks.disconnect('my_signal', my_callback)
diff --git a/doc/release/next_whats_new/color_cycle_from_sequence.rst b/doc/release/next_whats_new/color_cycle_from_sequence.rst
deleted file mode 100644
index 0f9214c6fce3..000000000000
--- a/doc/release/next_whats_new/color_cycle_from_sequence.rst
+++ /dev/null
@@ -1,9 +0,0 @@
-Setting the default color cycle to a named color sequence
----------------------------------------------------------
-
-The default color cycle may now be configured in the ``matplotlibrc`` file or
-a style file to use any of the :doc:`/gallery/color/color_sequences`.  For example
-
-.. code-block:: none
-
-   axes.prop_cycle : cycler(color='Accent')
diff --git a/doc/release/next_whats_new/colormap_bad_under_over.rst b/doc/release/next_whats_new/colormap_bad_under_over.rst
deleted file mode 100644
index 772d47e4123d..000000000000
--- a/doc/release/next_whats_new/colormap_bad_under_over.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-Colormaps support giving colors for bad, under and over values on creation
---------------------------------------------------------------------------
-
-Colormaps gained keyword arguments ``bad``, ``under``, and ``over`` to
-specify these values on creation. Previously, these values would have to
-be set afterwards using one of `~.Colormap.set_bad`, `~.Colormap.set_under`,
-`~.Colormap.set_bad`, `~.Colormap.set_extremes`, `~.Colormap.with_extremes`.
-
-It is recommended to use the new functionality, e.g.::
-
-    cmap = ListedColormap(colors, bad="red", under="darkblue", over="purple")
-
-instead of::
-
-    cmap = ListedColormap(colors).with_extremes(
-        bad="red", under="darkblue", over="purple")
-
-or::
-
-   cmap = ListedColormap(colors)
-   cmap.set_bad("red")
-   cmap.set_under("darkblue")
-   cmap.set_over("purple")
diff --git a/doc/release/next_whats_new/colormap_with_alpha.rst b/doc/release/next_whats_new/colormap_with_alpha.rst
deleted file mode 100644
index 7bc9a84618a2..000000000000
--- a/doc/release/next_whats_new/colormap_with_alpha.rst
+++ /dev/null
@@ -1,5 +0,0 @@
-Tuning transparency of colormaps
---------------------------------
-The new method `.Colormap.with_alpha` allows to create a new colormap with the same
-color values but a new uniform alpha value. This is handy if you want to modify only
-the transparency of mapped colors for an Artist.
diff --git a/doc/release/next_whats_new/cycler_rcparam_security.rst b/doc/release/next_whats_new/cycler_rcparam_security.rst
deleted file mode 100644
index e4e2893aa994..000000000000
--- a/doc/release/next_whats_new/cycler_rcparam_security.rst
+++ /dev/null
@@ -1,14 +0,0 @@
-``axes.prop_cycle`` rcParam security improvements
--------------------------------------------------
-
-The ``axes.prop_cycle`` rcParam is now parsed in a safer and more restricted
-manner. Only literals, ``cycler()`` and ``concat()`` calls, the operators
-``+`` and ``*``, and slicing are allowed. All previously valid cycler strings
-documented at https://matplotlib.org/cycler/ are still supported, for example:
-
-.. code-block:: none
-
-   axes.prop_cycle : cycler('color', ['r', 'g', 'b']) + cycler('linewidth', [1, 2, 3])
-   axes.prop_cycle : 2 * cycler('color', 'rgb')
-   axes.prop_cycle : concat(cycler('color', 'rgb'), cycler('color', 'cmk'))
-   axes.prop_cycle : cycler('color', 'rgbcmk')[:3]
diff --git a/doc/release/next_whats_new/depthshading_improvement.rst b/doc/release/next_whats_new/depthshading_improvement.rst
deleted file mode 100644
index 8e5c04e84b8c..000000000000
--- a/doc/release/next_whats_new/depthshading_improvement.rst
+++ /dev/null
@@ -1,39 +0,0 @@
-3D depth-shading fix
---------------------
-
-Previously, a slightly buggy method of estimating the visual "depth" of 3D
-items could lead to sudden and unexpected changes in transparency as the plot
-orientation changed.
-
-Now, the behavior has been made smooth and predictable. A new parameter
-``depthshade_minalpha`` has also been added to allow users to set the minimum
-transparency level. Depth-shading is an option for Patch3DCollections and
-Path3DCollections, including 3D scatter plots.
-
-The default values for ``depthshade`` and ``depthshade_minalpha`` are now also
-controlled via rcParams, with values of ``True`` and ``0.3`` respectively.
-
-A simple example:
-
-.. plot::
-    :include-source: true
-    :alt: A 3D scatter plot with depth-shading enabled.
-
-    import matplotlib.pyplot as plt
-
-    fig = plt.figure()
-    ax = fig.add_subplot(projection="3d")
-
-    X = [i for i in range(10)]
-    Y = [i for i in range(10)]
-    Z = [i for i in range(10)]
-    S = [(i + 1) * 400 for i in range(10)]
-
-    ax.scatter(
-        xs=X, ys=Y, zs=Z, s=S,
-        depthshade=True,
-        depthshade_minalpha=0.3,
-    )
-    ax.view_init(elev=10, azim=-150, roll=0)
-
-    plt.show()
diff --git a/doc/release/next_whats_new/figsize_unit.rst b/doc/release/next_whats_new/figsize_unit.rst
deleted file mode 100644
index ded95d9930a5..000000000000
--- a/doc/release/next_whats_new/figsize_unit.rst
+++ /dev/null
@@ -1,9 +0,0 @@
-Figure size units
------------------
-
-When creating figures, it is now possible to define figure sizes in cm or pixel.
-
-Up to now the figure size is specified via ``plt.figure(..., figsize=(6, 4))``,
-and the given numbers are interpreted as inches. It is now possible to add a
-unit string to the tuple, i.e. ``plt.figure(..., figsize=(600, 400, "px"))``.
-Supported unit strings are "in", "cm", "px".
diff --git a/doc/release/next_whats_new/font_alt_family_names.rst b/doc/release/next_whats_new/font_alt_family_names.rst
deleted file mode 100644
index 11b67bf6d584..000000000000
--- a/doc/release/next_whats_new/font_alt_family_names.rst
+++ /dev/null
@@ -1,25 +0,0 @@
-Fonts addressable by all their SFNT family names
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-Fonts can now be selected by any of the family names they advertise in
-the OpenType name table, not just the one FreeType reports as the primary
-family name.
-
-Some fonts store different family names on different platforms or in
-different name-table entries.  For example, Ubuntu Light stores
-``"Ubuntu"`` in the Macintosh-platform Name ID 1 slot (which FreeType
-uses as the primary name) and ``"Ubuntu Light"`` in the Microsoft-platform
-Name ID 1 slot.  Previously only the FreeType-derived name was registered,
-requiring an obscure weight-based workaround::
-
-    # Previously required
-    matplotlib.rcParams['font.family'] = 'Ubuntu'
-    matplotlib.rcParams['font.weight'] = 300
-
-All name-table entries that describe a family — Name ID 1 on both
-platforms, the Typographic Family (Name ID 16), and the WWS Family
-(Name ID 21) — are now registered as separate entries in the
-`~matplotlib.font_manager.FontManager`, so any of those names can be
-used directly::
-
-    matplotlib.rcParams['font.family'] = 'Ubuntu Light'
diff --git a/doc/release/next_whats_new/font_features.rst b/doc/release/next_whats_new/font_features.rst
deleted file mode 100644
index 022d36e1e21d..000000000000
--- a/doc/release/next_whats_new/font_features.rst
+++ /dev/null
@@ -1,41 +0,0 @@
-Specifying font feature tags
-----------------------------
-
-OpenType fonts may support feature tags that specify alternate glyph shapes or
-substitutions to be made optionally. The text API now supports setting a list of feature
-tags to be used with the associated font. Feature tags can be set/get with:
-
-- `matplotlib.text.Text.set_fontfeatures` / `matplotlib.text.Text.get_fontfeatures`
-- Any API that creates a `.Text` object by passing the *fontfeatures* argument (e.g.,
-  ``plt.xlabel(..., fontfeatures=...)``)
-
-Font feature strings are eventually passed to HarfBuzz, and so all `string formats
-supported by hb_feature_from_string()
-<https://harfbuzz.github.io/harfbuzz-hb-common.html#hb-feature-from-string>`__ are
-supported. Note though that subranges are not explicitly supported and behaviour may
-change in the future.
-
-For example, the default font ``DejaVu Sans`` enables Standard Ligatures (the ``'liga'``
-tag) by default, and also provides optional Discretionary Ligatures (the ``dlig`` tag.)
-These may be toggled with ``+`` or ``-``.
-
-.. plot::
-    :include-source:
-
-    fig = plt.figure(figsize=(7, 3))
-
-    fig.text(0.5, 0.85, 'Ligatures', fontsize=40, horizontalalignment='center')
-
-    # Default has Standard Ligatures (liga).
-    fig.text(0, 0.6, 'Default: fi ffi fl st', fontsize=40)
-
-    # Disable Standard Ligatures with -liga.
-    fig.text(0, 0.35, 'Disabled: fi ffi fl st', fontsize=40,
-             fontfeatures=['-liga'])
-
-    # Enable Discretionary Ligatures with dlig.
-    fig.text(0, 0.1, 'Discretionary: fi ffi fl st', fontsize=40,
-             fontfeatures=['dlig'])
-
-Available font feature tags may be found at
-https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist
diff --git a/doc/release/next_whats_new/gif_savefig.rst b/doc/release/next_whats_new/gif_savefig.rst
deleted file mode 100644
index e6f4732e8b95..000000000000
--- a/doc/release/next_whats_new/gif_savefig.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-Saving figures as GIF works again
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-According to the figure documentation, the ``savefig`` method supports the
-GIF format with the file extension ``.gif``. However, GIF support had been
-broken since Matplotlib 2.0.0. It works again.
diff --git a/doc/release/next_whats_new/grouped_bar.rst b/doc/release/next_whats_new/grouped_bar.rst
deleted file mode 100644
index af57c71b8a3a..000000000000
--- a/doc/release/next_whats_new/grouped_bar.rst
+++ /dev/null
@@ -1,26 +0,0 @@
-Grouped bar charts
-------------------
-
-The new method `~.Axes.grouped_bar()` simplifies the creation of grouped bar charts
-significantly. It supports different input data types (lists of datasets, dicts of
-datasets, data in 2D arrays, pandas DataFrames), and allows for easy customization
-of placement via controllable distances between bars and between bar groups.
-
-Example:
-
-.. plot::
-    :include-source: true
-    :alt: Diagram of a grouped bar chart of 3 datasets with 2 categories.
-
-    import matplotlib.pyplot as plt
-
-    categories = ['A', 'B']
-    datasets = {
-        'dataset 0': [1, 11],
-        'dataset 1': [3, 13],
-        'dataset 2': [5, 15],
-    }
-
-    fig, ax = plt.subplots()
-    ax.grouped_bar(datasets, tick_labels=categories)
-    ax.legend()
diff --git a/doc/release/next_whats_new/hist_color.rst b/doc/release/next_whats_new/hist_color.rst
deleted file mode 100644
index 2d6a4adb3464..000000000000
--- a/doc/release/next_whats_new/hist_color.rst
+++ /dev/null
@@ -1,5 +0,0 @@
-``hist()`` supports a single color for multiple datasets
---------------------------------------------------------
-
-It is now possible to pass a single *color* value to `~.Axes.hist()`. This
-value is applied to all datasets.
diff --git a/doc/release/next_whats_new/ignore_system_fonts.rst b/doc/release/next_whats_new/ignore_system_fonts.rst
deleted file mode 100644
index a04c1d025d90..000000000000
--- a/doc/release/next_whats_new/ignore_system_fonts.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-New environment variable to ignore system fonts
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-System fonts may be ignored by setting the :envvar:`MPL_IGNORE_SYSTEM_FONTS`; this
-suppresses searching for system fonts (in known directories or via some
-platform-specific subprocess) as well as limiting the results from `.FontManager.findfont`.
diff --git a/doc/release/next_whats_new/last_resort_font.rst b/doc/release/next_whats_new/last_resort_font.rst
deleted file mode 100644
index 307d4c2b8558..000000000000
--- a/doc/release/next_whats_new/last_resort_font.rst
+++ /dev/null
@@ -1,40 +0,0 @@
-Missing glyphs use Last Resort font
------------------------------------
-
-Most fonts do not have 100% character coverage, and will fall back to a "not found"
-glyph for characters that are not provided. Often, this glyph will be minimal (e.g., the
-default DejaVu Sans "not found" glyph is just a rectangle.) Such minimal glyphs provide
-no context as to the characters that are missing.
-
-Now, missing glyphs will fall back to the `Last Resort font
-<https://github.com/unicode-org/last-resort-font>`__ produced by the Unicode Consortium.
-This special-purpose font provides glyphs that represent types of Unicode characters.
-These glyphs show a representative character from the missing Unicode block, and at
-larger sizes, more context to help determine which character and font are needed.
-
-To disable this fallback behaviour, set :rc:`font.enable_last_resort` to ``False``.
-
-.. plot::
-    :alt: An example of missing glyph behaviour, the first glyph from Bengali script,
-        second glyph from Hiragana, and the last glyph from the Unicode Private Use
-        Area. Multiple lines repeat the text with increasing font size from top to
-        bottom.
-
-    text_raw = r"'\N{Bengali Digit Zero}\N{Hiragana Letter A}\ufdd0'"
-    text = eval(text_raw)
-    sizes = [
-        (0.85, 8),
-        (0.80, 10),
-        (0.75, 12),
-        (0.70, 16),
-        (0.63, 20),
-        (0.55, 24),
-        (0.45, 32),
-        (0.30, 48),
-        (0.10, 64),
-    ]
-
-    fig = plt.figure()
-    fig.text(0.01, 0.90, f'Input: {text_raw}')
-    for y, size in sizes:
-        fig.text(0.01, y, f'{size}pt:{text}', fontsize=size)
diff --git a/doc/release/next_whats_new/legend_line_width.rst b/doc/release/next_whats_new/legend_line_width.rst
deleted file mode 100644
index d8cfd57640a8..000000000000
--- a/doc/release/next_whats_new/legend_line_width.rst
+++ /dev/null
@@ -1,21 +0,0 @@
-``legend.linewidth`` rcParam and parameter
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-A new rcParam ``legend.linewidth`` has been added to control the line width of
-the legend's box edges. When set to ``None`` (the default), it inherits the
-value from ``patch.linewidth``. This allows for independent control of the
-legend frame line width without affecting other elements.
-
-The `.Legend` constructor also accepts a new *linewidth* parameter to set the
-legend frame line width directly, overriding the rcParam value.
-
-.. plot::
-    :include-source: true
-    :alt: A line plot with a legend showing a thick border around the legend box.
-
-    import matplotlib.pyplot as plt
-
-    fig, ax = plt.subplots()
-    ax.plot([1, 2, 3], label='data')
-    ax.legend(linewidth=2.0)  # Thick legend box edge
-    plt.show()
diff --git a/doc/release/next_whats_new/libraqm.rst b/doc/release/next_whats_new/libraqm.rst
deleted file mode 100644
index 8312f2f9432c..000000000000
--- a/doc/release/next_whats_new/libraqm.rst
+++ /dev/null
@@ -1,42 +0,0 @@
-Complex text layout with libraqm
---------------------------------
-
-Text support has been extended to include complex text layout. This support includes:
-
-1. Languages that require advanced layout, such as Arabic or Hebrew.
-2. Text that mixes left-to-right and right-to-left languages.
-
-   .. plot::
-       :show-source-link: False
-
-       text = 'Here is some رَقْم in اَلْعَرَبِيَّةُ'
-       fig = plt.figure(figsize=(6, 1))
-       fig.text(0.5, 0.5, text, size=32, ha='center', va='center')
-
-3. Ligatures that combine several adjacent characters for improved legibility.
-
-   .. plot::
-       :show-source-link: False
-
-       text = 'f\N{Hair Space}f\N{Hair Space}i \N{Rightwards Arrow} ffi'
-       fig = plt.figure(figsize=(3, 1))
-       fig.text(0.5, 0.5, text, size=32, ha='center', va='center')
-
-4. Combining multiple or double-width diacritics.
-
-   .. plot::
-       :show-source-link: False
-
-       text = (
-           'a\N{Combining Circumflex Accent}\N{Combining Double Tilde}'
-           'c\N{Combining Diaeresis}')
-       text = ' + '.join(
-           c if c in 'ac' else f'\N{Dotted Circle}{c}'
-           for c in text) + f' \N{Rightwards Arrow} {text}'
-       fig = plt.figure(figsize=(6, 1))
-       fig.text(0.5, 0.5, text, size=32, ha='center', va='center',
-                # Builtin DejaVu Sans doesn't support multiple diacritics.
-                family=['Noto Sans', 'DejaVu Sans'])
-
-Note, all advanced features require corresponding font support, and may require
-additional fonts over the builtin DejaVu Sans.
diff --git a/doc/release/next_whats_new/log_contour_levels.rst b/doc/release/next_whats_new/log_contour_levels.rst
deleted file mode 100644
index da5cc2da6070..000000000000
--- a/doc/release/next_whats_new/log_contour_levels.rst
+++ /dev/null
@@ -1,4 +0,0 @@
-Maximum levels on log-scaled contour plots are now respected
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-When plotting contours with a log norm, passing an integer value to the ``levels``
-argument to cap the maximum number of contour levels now works as intended.
diff --git a/doc/release/next_whats_new/logticks.rst b/doc/release/next_whats_new/logticks.rst
deleted file mode 100644
index b729cd990f91..000000000000
--- a/doc/release/next_whats_new/logticks.rst
+++ /dev/null
@@ -1,11 +0,0 @@
-Improved selection of log-scale ticks
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-The algorithm for selecting log-scale ticks (on powers of ten) has been
-improved.  In particular, it will now always draw as many ticks as possible
-(e.g., it will not draw a single tick if it was possible to fit two ticks); if
-subsampling ticks, it will prefer putting ticks on integer multiples of the
-subsampling stride (e.g., it prefers putting ticks at 10\ :sup:`0`, 10\ :sup:`3`,
-10\ :sup:`6` rather than 10\ :sup:`1`, 10\ :sup:`4`, 10\ :sup:`7`) if this
-results in the same number of ticks at the end; and it is now more robust
-against floating-point calculation errors.
diff --git a/doc/release/next_whats_new/mathnormal.rst b/doc/release/next_whats_new/mathnormal.rst
deleted file mode 100644
index 7e4cd5d333fe..000000000000
--- a/doc/release/next_whats_new/mathnormal.rst
+++ /dev/null
@@ -1,10 +0,0 @@
-Mathtext distinguishes *italic* and *normal* font
--------------------------------------------------
-
-Matplotlib's lightweight TeX expression parser (``usetex=False``) now distinguishes between *italic* and *normal* math fonts to closer replicate the behaviour of LaTeX.
-The normal math font is selected by default in math environment (unless the rcParam ``mathtext.default`` is overwritten) but can be explicitly set with the new ``\mathnormal`` command. Italic font is selected with ``\mathit``.
-The main difference is that *italic* produces italic digits, whereas *normal* produces upright digits. Previously, it was not possible to typeset italic digits.
-Note that ``normal`` now corresponds to what used to be ``it``, whereas ``it`` now renders all characters italic.
-**Important**: In case the default mathematics font is overwritten by setting ``mathtext.default: it`` in ``matplotlibrc``, it must be either commented out or changed to ``mathtext.default: normal`` to preserve its behaviour. Otherwise, all alphanumeric characters, including digits, are rendered italic.
-
-One difference to traditional LaTeX is that LaTeX further distinguishes between *normal* (``\mathnormal``) and *default math*, where the default uses roman digits and normal uses oldstyle digits. This distinction is no longer present with modern LaTeX engines and unicode-math nor in Matplotlib.
diff --git a/doc/release/next_whats_new/new_rcparams_grid_options.rst b/doc/release/next_whats_new/new_rcparams_grid_options.rst
deleted file mode 100644
index c2c0455eecbb..000000000000
--- a/doc/release/next_whats_new/new_rcparams_grid_options.rst
+++ /dev/null
@@ -1,33 +0,0 @@
-Separate styling options for major/minor grid line in rcParams
---------------------------------------------------------------
-
-Using :rc:`grid.major.*` or :rc:`grid.minor.*` will overwrite the value in
-:rc:`grid.*` for the major and minor gridlines, respectively.
-
-.. plot::
-    :include-source: true
-    :alt: Modifying the gridlines using the new options `rcParams`
-
-    import matplotlib as mpl
-    import matplotlib.pyplot as plt
-
-
-    # Set visibility for major and minor gridlines
-    mpl.rcParams["axes.grid"] = True
-    mpl.rcParams["ytick.minor.visible"] = True
-    mpl.rcParams["xtick.minor.visible"] = True
-    mpl.rcParams["axes.grid.which"] = "both"
-
-    # Using old values to set both major and minor properties
-    mpl.rcParams["grid.color"] = "red"
-    mpl.rcParams["grid.linewidth"] = 1
-
-    # Overwrite some values for major and minor separately
-    mpl.rcParams["grid.major.color"] = "black"
-    mpl.rcParams["grid.major.linewidth"] = 2
-    mpl.rcParams["grid.minor.linestyle"] = ":"
-    mpl.rcParams["grid.minor.alpha"] = 0.6
-
-    plt.plot([0, 1], [0, 1])
-
-    plt.show()
diff --git a/doc/release/next_whats_new/okabe_ito_colormap.rst b/doc/release/next_whats_new/okabe_ito_colormap.rst
deleted file mode 100644
index fad461257932..000000000000
--- a/doc/release/next_whats_new/okabe_ito_colormap.rst
+++ /dev/null
@@ -1,29 +0,0 @@
-Okabe-Ito accessible color sequence
------------------------------------
-
-Matplotlib now includes the `Okabe-Ito color sequence`_. Its colors remain distinguishable for common forms of color-vision deficiency and when printed.
-
-.. _Okabe-Ito color sequence: https://jfly.uni-koeln.de/color/#pallet
-
-For example, to set it as the default colormap for your plots and image-like artists, use:
-
-.. code-block:: python
-
-    import matplotlib.pyplot as plt
-    from cycler import cycler
-
-    plt.rcParams['axes.prop_cycle'] = cycler('color', plt.colormaps['okabe_ito'].colors)
-    plt.rcParams['image.cmap'] = 'okabe_ito'
-
-Or, when creating plots, you can pass it explicitly:
-
-.. plot::
-
-    import matplotlib.pyplot as plt
-
-    colors = plt.colormaps['okabe_ito'].colors
-    x = range(5)
-    for i, c in enumerate(colors):
-        plt.plot(x, [v*(i+1) for v in x], color=c, label=f'line {i}')
-    plt.legend()
-    plt.show()
diff --git a/doc/release/next_whats_new/partial_figsize_none.rst b/doc/release/next_whats_new/partial_figsize_none.rst
deleted file mode 100644
index 43bd3e34cc73..000000000000
--- a/doc/release/next_whats_new/partial_figsize_none.rst
+++ /dev/null
@@ -1,12 +0,0 @@
-Partial ``figsize`` specification at figure creation
-----------------------------------------------------
-
-Figure creation now accepts a single ``None`` in ``figsize``.
-Passing ``(None, h)`` uses the default width from :rc:`figure.figsize`, and
-passing ``(w, None)`` uses the default height.
-Passing ``(None, None)`` is invalid and raises a `ValueError`.
-
-For example::
-
-    import matplotlib.pyplot as plt
-    fig = plt.figure(figsize=(None, 4))
diff --git a/doc/release/next_whats_new/patch_edgegapcolor.rst b/doc/release/next_whats_new/patch_edgegapcolor.rst
deleted file mode 100644
index b981116fbb76..000000000000
--- a/doc/release/next_whats_new/patch_edgegapcolor.rst
+++ /dev/null
@@ -1,24 +0,0 @@
-``edgegapcolor`` for Patches
-----------------------------
-
-`~matplotlib.patches.Patch` now supports an *edgegapcolor* parameter,
-similar to the existing *gapcolor* in `.Line2D`. This allows patches with
-dashed edges to display a secondary color in the gaps, creating a "striped"
-edge effect.
-
-This is useful when drawing unfilled patches on backgrounds of unknown color,
-where alternating edge colors ensure the patch boundary remains visible.
-
-.. plot::
-    :include-source: true
-    :alt: A rectangle with a dashed orange edge and blue gaps, demonstrating the edgegapcolor feature.
-
-    import matplotlib.pyplot as plt
-    from matplotlib.patches import Rectangle
-
-    fig, ax = plt.subplots()
-    rect = Rectangle((0.1, 0.1), 0.6, 0.6, fill=False,
-                      edgecolor='orange', edgegapcolor='blue',
-                      linestyle='--', linewidth=3)
-    ax.add_patch(rect)
-    plt.show()
diff --git a/doc/release/next_whats_new/patchcollection_legend.rst b/doc/release/next_whats_new/patchcollection_legend.rst
deleted file mode 100644
index 58574e9e6757..000000000000
--- a/doc/release/next_whats_new/patchcollection_legend.rst
+++ /dev/null
@@ -1,22 +0,0 @@
-``PatchCollection`` legends now supported
-------------------------------------------
-`.PatchCollection` instances now properly display in legends when given a label.
-Previously, labels on `~.PatchCollection` objects were ignored by the legend
-system, requiring users to create manual legend entries.
-
-.. plot::
-   :include-source: true
-   :alt: The legend entry displays a rectangle matching the visual properties (colors, line styles, line widths) of the first patch in the collection.
-
-    import matplotlib.pyplot as plt
-    import matplotlib.patches as mpatches
-    from matplotlib.collections import PatchCollection
-
-    fig, ax = plt.subplots()
-    patches = [mpatches.Circle((0, 0), 0.1), mpatches.Rectangle((0.5, 0.5), 0.2, 0.3)]
-    pc = PatchCollection(patches, facecolor='blue', edgecolor='black', label='My patches')
-    ax.add_collection(pc)
-    ax.legend()  # Now displays the label "My patches"
-    plt.show()
-
-This fix resolves :ghissue:`23998`.
diff --git a/doc/release/next_whats_new/pdf_fonts.rst b/doc/release/next_whats_new/pdf_fonts.rst
deleted file mode 100644
index 4d8665386a72..000000000000
--- a/doc/release/next_whats_new/pdf_fonts.rst
+++ /dev/null
@@ -1,10 +0,0 @@
-Improved font embedding in PDF
-------------------------------
-
-Both Type 3 and Type 42 fonts (see :ref:`fonts` for more details) are now
-embedded into PDFs without limitation. Fonts may be split into multiple
-embedded subsets in order to satisfy format limits. Additionally, a corrected
-Unicode mapping is added for each.
-
-This means that *all* text should now be selectable and copyable in PDF viewers
-that support doing so.
diff --git a/doc/release/next_whats_new/pie_label.rst b/doc/release/next_whats_new/pie_label.rst
deleted file mode 100644
index 6dc9a3f619c2..000000000000
--- a/doc/release/next_whats_new/pie_label.rst
+++ /dev/null
@@ -1,28 +0,0 @@
-Adding labels to pie chart wedges
----------------------------------
-
-The new `~.Axes.pie_label` method adds a label to each wedge in a pie chart created with
-`~.Axes.pie`.  It can take
-
-* a list of strings, similar to the existing *labels* parameter of `~.Axes.pie`
-* a format string similar to the existing *autopct* parameter of `~.Axes.pie` except
-  that it uses the `str.format` method and it can handle absolute values as well as
-  fractions/percentages
-
-For more examples, see :doc:`/gallery/pie_and_polar_charts/pie_label`.
-
-.. plot::
-    :include-source: true
-    :alt: A pie chart with three labels on each wedge, showing a food type, number, and fraction associated with the wedge.
-
-    import matplotlib.pyplot as plt
-
-    data = [36, 24, 8, 12]
-    labels = ['spam', 'eggs', 'bacon', 'sausage']
-
-    fig, ax = plt.subplots()
-    pie = ax.pie(data)
-
-    ax.pie_label(pie, labels, distance=1.1)
-    ax.pie_label(pie, '{frac:.1%}', distance=0.7)
-    ax.pie_label(pie, '{absval:d}', distance=0.4)
diff --git a/doc/release/next_whats_new/pyplot-register-figure.rst b/doc/release/next_whats_new/pyplot-register-figure.rst
deleted file mode 100644
index 86ffcbf2294a..000000000000
--- a/doc/release/next_whats_new/pyplot-register-figure.rst
+++ /dev/null
@@ -1,63 +0,0 @@
-Figures can be attached to and removed from pyplot
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-Figures can now be attached to and removed from management through pyplot, which in
-the background also means a less strict coupling to backends.
-
-In particular, standalone figures (created with the `.Figure` constructor) can now be
-registered with the `.pyplot` module by calling ``plt.figure(fig)``. This allows to
-show them with ``plt.show()`` as you would do with any figure created with pyplot
-factory methods such as ``plt.figure()`` or ``plt.subplots()``.
-
-When closing a shown figure window, the related figure is reset to the standalone
-state, i.e. it's not visible to pyplot anymore, but if you still hold a reference
-to it, you can continue to work with it (e.g. do ``fig.savefig()``, or re-add it
-to pyplot with ``plt.figure(fig)`` and then show it again).
-
-The following is now possible - though the example is exaggerated to show what's
-possible. In practice, you'll stick with much simpler versions for better
-consistency ::
-
-    import matplotlib.pyplot as plt
-    from matplotlib.figure import Figure
-
-    # Create a standalone figure
-    fig = Figure()
-    ax = fig.add_subplot()
-    ax.plot([1, 2, 3], [4, 5, 6])
-
-    # Register it with pyplot
-    plt.figure(fig)
-
-    # Modify the figure through pyplot
-    plt.xlabel("x label")
-
-    # Show the figure
-    plt.show()
-
-    # Close the figure window through the GUI
-
-    # Continue to work on the figure
-    fig.savefig("my_figure.png")
-    ax.set_ylabel("y label")
-
-    # Re-register the figure and show it again
-    plt.figure(fig)
-    plt.show()
-
-Technical detail: Standalone figures use `.FigureCanvasBase` as canvas. This is
-replaced by a backend-dependent subclass when registering with pyplot, and is
-reset to `.FigureCanvasBase` when the figure is closed. `.Figure.savefig` uses
-the current canvas to save the figure (if possible). Since `.FigureCanvasBase`
-can not render the figure, when saving the figure, it will fallback to a suitable
-canvas subclass, e.g. `.FigureCanvasAgg` for raster outputs such as png.
-Any Agg-based backend will create the same file output. However, there may be
-slight differences for non-Agg backends; e.g. if you use "GTK4Cairo" as
-interactive backend, ``fig.savefig("file.png")`` may create a slightly different
-image depending on whether the figure is registered with pyplot or not. In
-general, you should not store a reference to the canvas, but rather always
-obtain it from the figure with ``fig.canvas``. This will return the current
-canvas, which is either the original `.FigureCanvasBase` or a backend-dependent
-subclass, depending on whether the figure is registered with pyplot or not.
-Additionally, the swapping of the canvas currently does not play well with
-blitting of matplotlib widgets; in such cases either deactivate blitting or do not
-continue to use the figure (e.g. saving it after closing the window).
diff --git a/doc/release/next_whats_new/radio_buttons_2d_grid.rst b/doc/release/next_whats_new/radio_buttons_2d_grid.rst
deleted file mode 100644
index 3840eb69211e..000000000000
--- a/doc/release/next_whats_new/radio_buttons_2d_grid.rst
+++ /dev/null
@@ -1,54 +0,0 @@
-RadioButtons and CheckButtons widgets support flexible layouts
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-The `.widgets.RadioButtons` and `.widgets.CheckButtons` widgets now support
-arranging buttons in different layouts via the new *layout* parameter. You can
-arrange buttons vertically (default), horizontally, or in a 2D grid by passing
-a ``(rows, cols)`` tuple.
-
-See :doc:`/gallery/widgets/radio_buttons_grid` for a ``(rows, cols)`` example.
-
-.. plot::
-    :include-source: true
-    :alt: Multiple sine waves with checkboxes to toggle their visibility.
-
-    import matplotlib.pyplot as plt
-    import numpy as np
-    from matplotlib.widgets import CheckButtons
-
-    t = np.arange(0.0, 2.0, 0.01)
-    s0 = np.sin(2*np.pi*t)
-    s1 = np.sin(4*np.pi*t)
-    s2 = np.sin(6*np.pi*t)
-    s3 = np.sin(8*np.pi*t)
-
-    fig, axes = plt.subplot_mosaic(
-        [['main'], ['buttons']],
-        height_ratios=[8, 1],
-        layout="constrained",
-    )
-
-    l0, = axes['main'].plot(t, s0, lw=2, color='red', label='2 Hz')
-    l1, = axes['main'].plot(t, s1, lw=2, color='green', label='4 Hz')
-    l2, = axes['main'].plot(t, s2, lw=2, color='blue', label='6 Hz')
-    l3, = axes['main'].plot(t, s3, lw=2, color='purple', label='8 Hz')
-    axes['main'].set_xlabel('Time (s)')
-    axes['main'].set_ylabel('Amplitude')
-
-    lines_by_label = {l.get_label(): l for l in [l0, l1, l2, l3]}
-
-    axes['buttons'].set_facecolor('0.9')
-    check = CheckButtons(
-        axes['buttons'],
-        labels=lines_by_label.keys(),
-        actives=[l.get_visible() for l in lines_by_label.values()],
-        layout='horizontal'
-    )
-
-    def callback(label):
-        ln = lines_by_label[label]
-        ln.set_visible(not ln.get_visible())
-        fig.canvas.draw_idle()
-
-    check.on_clicked(callback)
-    plt.show()
diff --git a/doc/release/next_whats_new/scroll_to_zoom.rst b/doc/release/next_whats_new/scroll_to_zoom.rst
deleted file mode 100644
index 1be522b7a255..000000000000
--- a/doc/release/next_whats_new/scroll_to_zoom.rst
+++ /dev/null
@@ -1,9 +0,0 @@
-Zooming using mouse wheel
-~~~~~~~~~~~~~~~~~~~~~~~~~
-
-``Ctrl+MouseWheel`` can be used to zoom in the plot windows.
-Additionally, ``x+MouseWheel`` zooms only the x-axis and ``y+MouseWheel`` zooms only the y-axis.
-
-The zoom focusses on the mouse pointer. With ``Ctrl``, the axes aspect ratio is kept; with ``x`` or ``y``, only the respective axis is scaled.
-
-Zooming is currently only supported on rectilinear Axes.
diff --git a/doc/release/next_whats_new/separated_hatchcolor.rst b/doc/release/next_whats_new/separated_hatchcolor.rst
deleted file mode 100644
index a794fba2e515..000000000000
--- a/doc/release/next_whats_new/separated_hatchcolor.rst
+++ /dev/null
@@ -1,95 +0,0 @@
-Separated ``hatchcolor`` from ``edgecolor``
--------------------------------------------
-
-When the *hatchcolor* parameter is specified, it will be used for the hatch.
-If it is not specified, it will fall back to using :rc:`hatch.color`.
-The special value 'edge' uses the patch edgecolor, with a fallback to
-:rc:`patch.edgecolor` if the patch edgecolor is 'none'.
-Previously, hatch colors were the same as edge colors, with a fallback to
-:rc:`hatch.color` if the patch did not have an edge color.
-
-.. plot::
-    :include-source: true
-    :alt: Four Rectangle patches, each displaying the color of hatches in different specifications of edgecolor and hatchcolor. Top left has hatchcolor='black' representing the default value when both hatchcolor and edgecolor are not set, top right has edgecolor='blue' and hatchcolor='black' which remains when the edgecolor is set again, bottom left has edgecolor='red' and hatchcolor='orange' on explicit specification and bottom right has edgecolor='green' and hatchcolor='green' when the hatchcolor is not set.
-
-    import matplotlib as mpl
-    import matplotlib.pyplot as plt
-    from matplotlib.patches import Rectangle
-
-    fig, ax = plt.subplots()
-
-    # In this case, hatchcolor is orange
-    patch1 = Rectangle((0.1, 0.1), 0.3, 0.3, edgecolor='red', linewidth=2,
-                       hatch='//', hatchcolor='orange')
-    ax.add_patch(patch1)
-
-    # When hatchcolor is not specified, it matches edgecolor
-    # In this case, hatchcolor is green
-    patch2 = Rectangle((0.6, 0.1), 0.3, 0.3, edgecolor='green', linewidth=2,
-                       hatch='//', facecolor='none')
-    ax.add_patch(patch2)
-
-    # If both hatchcolor and edgecolor are not specified
-    # it will default to the 'patch.edgecolor' rcParam, which is black by default
-    # In this case, hatchcolor is black
-    patch3 = Rectangle((0.1, 0.6), 0.3, 0.3, hatch='//')
-    ax.add_patch(patch3)
-
-    # When using `hatch.color` in the `rcParams`
-    # edgecolor will now not overwrite hatchcolor
-    # In this case, hatchcolor is black
-    with plt.rc_context({'hatch.color': 'black'}):
-        patch4 = Rectangle((0.6, 0.6), 0.3, 0.3, edgecolor='blue', linewidth=2,
-                           hatch='//', facecolor='none')
-
-    # hatchcolor is black (it uses the `hatch.color` rcParam value)
-    patch4.set_edgecolor('blue')
-    # hatchcolor is still black (here, it does not update when edgecolor changes)
-    ax.add_patch(patch4)
-
-    ax.annotate("hatchcolor = 'orange'",
-                xy=(.5, 1.03), xycoords=patch1, ha='center', va='bottom')
-    ax.annotate("hatch color unspecified\nedgecolor='green'",
-                xy=(.5, 1.03), xycoords=patch2, ha='center', va='bottom')
-    ax.annotate("hatch color unspecified\nusing patch.edgecolor",
-                xy=(.5, 1.03), xycoords=patch3, ha='center', va='bottom')
-    ax.annotate("hatch.color='black'",
-                xy=(.5, 1.03), xycoords=patch4, ha='center', va='bottom')
-
-    plt.show()
-
-For collections, a sequence of colors can be passed to the *hatchcolor* parameter
-which will be cycled through for each hatch, similar to *facecolor* and *edgecolor*.
-
-Previously, if *edgecolor* was not specified, the hatch color would fall back to
-:rc:`patch.edgecolor`, but the alpha value would default to **1.0**, regardless of the
-alpha value of the collection. This behavior has been changed such that, if both
-*hatchcolor* and *edgecolor* are not specified, the hatch color will fall back
-to 'patch.edgecolor' with the alpha value of the collection.
-
-.. plot::
-    :include-source: true
-    :alt: A random scatter plot with hatches on the markers. The hatches are colored in blue, orange, and green, respectively. After the first three markers, the colors are cycled through again.
-
-    import matplotlib.pyplot as plt
-    import numpy as np
-
-    np.random.seed(19680801)
-
-    fig, ax = plt.subplots()
-
-    x = [29, 36, 41, 25, 32, 70, 62, 58, 66, 80, 58, 68, 62, 37, 48]
-    y = [82, 76, 48, 53, 62, 70, 84, 68, 55, 75, 29, 25, 12, 17, 20]
-    colors = ['tab:blue'] * 5 + ['tab:orange'] * 5 + ['tab:green'] * 5
-
-    ax.scatter(
-        x,
-        y,
-        s=800,
-        hatch="xxxx",
-        hatchcolor=colors,
-        facecolor="none",
-        edgecolor="black",
-    )
-
-    plt.show()
diff --git a/doc/release/next_whats_new/six_and_eight_color_petroff_color_cycles.rst b/doc/release/next_whats_new/six_and_eight_color_petroff_color_cycles.rst
deleted file mode 100644
index 3b17b4f68868..000000000000
--- a/doc/release/next_whats_new/six_and_eight_color_petroff_color_cycles.rst
+++ /dev/null
@@ -1,21 +0,0 @@
-Six and eight color Petroff color cycles
-----------------------------------------
-
-The six and eight color accessible Petroff color cycles are named 'petroff6' and
-'petroff8'.
-They compliment the existing 'petroff10' color cycle, added in `Matplotlib 3.10.0`_
-
-For more details see
-`Petroff, M. A.: "Accessible Color Sequences for Data Visualization"
-<https://arxiv.org/abs/2107.02270>`_.
-To load the 'petroff6' color cycle in place of the default::
-
-  import matplotlib.pyplot as plt
-  plt.style.use('petroff6')
-
-or to load the 'petroff8' color cycle::
-
-  import matplotlib.pyplot as plt
-  plt.style.use('petroff8')
-
-.. _Matplotlib 3.10.0: https://matplotlib.org/stable/users/prev_whats_new/whats_new_3.10.0.html#new-more-accessible-color-cycle
diff --git a/doc/release/next_whats_new/sliders_callable_valfmt.rst b/doc/release/next_whats_new/sliders_callable_valfmt.rst
deleted file mode 100644
index 1d350dba348a..000000000000
--- a/doc/release/next_whats_new/sliders_callable_valfmt.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-Callable *valfmt* for ``Slider`` and ``RangeSlider``
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-In addition to the existing %-format string, the *valfmt* parameter of
-`~.matplotlib.widgets.Slider` and `~.matplotlib.widgets.RangeSlider` now
-also accepts a callable of the form ``valfmt(val: float) -> str``.
diff --git a/doc/release/next_whats_new/snap_rotation.rst b/doc/release/next_whats_new/snap_rotation.rst
deleted file mode 100644
index 144a4fa96011..000000000000
--- a/doc/release/next_whats_new/snap_rotation.rst
+++ /dev/null
@@ -1,16 +0,0 @@
-Snapping 3D rotation angles with Control key
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-3D axes rotation now supports snapping to fixed angular increments
-when holding the ``Control`` key during mouse rotation.
-
-The snap step size is controlled by the new
-``axes3d.snap_rotation`` rcParam (default: 5.0 degrees).
-Setting it to 0 disables snapping.
-
-For example::
-
-    mpl.rcParams["axes3d.snap_rotation"] = 10
-
-will snap elevation, azimuth, and roll angles to multiples
-of 10 degrees while rotating with the mouse.
diff --git a/doc/release/next_whats_new/stackplot_style_sequences.rst b/doc/release/next_whats_new/stackplot_style_sequences.rst
deleted file mode 100644
index 209d30a15218..000000000000
--- a/doc/release/next_whats_new/stackplot_style_sequences.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-Stackplot styling
------------------
-
-`~.Axes.stackplot` now accepts sequences for the style parameters *facecolor*,
-*edgecolor*, *linestyle*, and *linewidth*, similar to how the *hatch* parameter
-is already handled.
diff --git a/doc/release/next_whats_new/streamplot_integration_control.rst b/doc/release/next_whats_new/streamplot_integration_control.rst
deleted file mode 100644
index 626bb33c8a95..000000000000
--- a/doc/release/next_whats_new/streamplot_integration_control.rst
+++ /dev/null
@@ -1,17 +0,0 @@
-Streamplot integration control
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-Two new options have been added to the `~.axes.Axes.streamplot` function that
-give the user better control of the streamline integration. The first is called
-``integration_max_step_scale`` and multiplies the default max step computed by the
-integrator. The second is called ``integration_max_error_scale`` and multiplies the
-default max error set by the integrator. Values for these parameters between
-zero and one reduce (tighten) the max step or error to improve streamline
-accuracy by performing more computation. Values greater than one increase
-(loosen) the max step or error to reduce computation time at the cost of lower
-streamline accuracy.
-
-The integrator defaults are both hand-tuned values and may not be applicable to
-all cases, so this allows customizing the behavior to specific use cases.
-Modifying only ``integration_max_step_scale`` has proved effective, but it may be useful
-to control the error as well.
diff --git a/doc/release/next_whats_new/streamplot_multiple_arrows.rst b/doc/release/next_whats_new/streamplot_multiple_arrows.rst
deleted file mode 100644
index 25329baa4a87..000000000000
--- a/doc/release/next_whats_new/streamplot_multiple_arrows.rst
+++ /dev/null
@@ -1,22 +0,0 @@
-Multiple arrows on a streamline
--------------------------------
-
-A new ``num_arrows`` argument has been added to `~matplotlib.axes.Axes.streamplot` that
-allows more than one arrow to be added to each streamline:
-
-.. plot::
-    :include-source: true
-    :alt: One chart showing a streamplot. Each streamline has three arrows.
-
-    import matplotlib.pyplot as plt
-    import numpy as np
-
-    w = 3
-    Y, X = np.mgrid[-w:w:100j, -w:w:100j]
-    U = -1 - X**2 + Y
-    V = 1 + X - Y**2
-
-    fig, ax = plt.subplots()
-    ax.streamplot(X, Y, U, V, num_arrows=3)
-
-    plt.show()
diff --git a/doc/release/next_whats_new/subplots_adjust.rst b/doc/release/next_whats_new/subplots_adjust.rst
deleted file mode 100644
index e0848ec8a3dc..000000000000
--- a/doc/release/next_whats_new/subplots_adjust.rst
+++ /dev/null
@@ -1,7 +0,0 @@
-Resetting the subplot parameters for figure.clear()
----------------------------------------------------
-
-When calling `.Figure.clear()` the settings for `.gridspec.SubplotParams` are restored to the default values.
-
-`~.SubplotParams.to_dict` is a new method to get the subplot parameters as a dict,
-and `~.SubplotParams.reset` resets the parameters to the defaults.
diff --git a/doc/release/next_whats_new/tex_phantoms.rst b/doc/release/next_whats_new/tex_phantoms.rst
deleted file mode 100644
index 82d39d502fb5..000000000000
--- a/doc/release/next_whats_new/tex_phantoms.rst
+++ /dev/null
@@ -1,11 +0,0 @@
-mathtext support for ``\phantom``, ``\llap``, ``\rlap``
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-mathtext gained support for the TeX macros ``\phantom``, ``\llap``, and
-``\rlap``. ``\phantom`` allows to occupy some space on the canvas as if
-some text was being rendered, without actually rendering that text, whereas
-``\llap`` and ``\rlap`` allows to render some text on the canvas while
-pretending that it occupies no space.  Altogether these macros allow some finer
-control of text alignments.
-
-See https://www.tug.org/TUGboat/tb22-4/tb72perlS.pdf for a detailed description
-of these macros.
diff --git a/doc/release/next_whats_new/text_language.rst b/doc/release/next_whats_new/text_language.rst
deleted file mode 100644
index 1d4668587b43..000000000000
--- a/doc/release/next_whats_new/text_language.rst
+++ /dev/null
@@ -1,37 +0,0 @@
-Specifying text language
-------------------------
-
-OpenType fonts may support language systems which can be used to select different
-typographic conventions, e.g., localized variants of letters that share a single Unicode
-code point, or different default font features. The text API now supports setting a
-language to be used and may be set/get with:
-
-- `matplotlib.text.Text.set_language` / `matplotlib.text.Text.get_language`
-- Any API that creates a `.Text` object by passing the *language* argument (e.g.,
-  ``plt.xlabel(..., language=...)``)
-
-The language of the text must be in a format accepted by libraqm, namely `a BCP47
-language code <https://www.w3.org/International/articles/language-tags/>`_. If None or
-unset, then no particular language will be implied, and default font settings will be
-used.
-
-For example, Matplotlib's default font ``DejaVu Sans`` supports language-specific glyphs
-in the Serbian and Macedonian languages in the Cyrillic alphabet (vs Russian),
-or the Sámi family of languages in the Latin alphabet (vs English).
-
-.. plot::
-    :include-source:
-
-    fig = plt.figure(figsize=(7, 3))
-
-    char = '\U00000431'
-    fig.text(0.5, 0.8, f'\\U{ord(char):08x}', fontsize=40, horizontalalignment='center')
-    fig.text(0, 0.6, f'Serbian: {char}', fontsize=40, language='sr')
-    fig.text(1, 0.6, f'Russian: {char}', fontsize=40, language='ru',
-             horizontalalignment='right')
-
-    char = '\U0000014a'
-    fig.text(0.5, 0.3, f'\\U{ord(char):08x}', fontsize=40, horizontalalignment='center')
-    fig.text(0, 0.1, f'Inari Sámi: {char}', fontsize=40, language='smn')
-    fig.text(1, 0.1, f'English: {char}', fontsize=40, language='en',
-             horizontalalignment='right')
diff --git a/doc/release/next_whats_new/ttc_fonts.rst b/doc/release/next_whats_new/ttc_fonts.rst
deleted file mode 100644
index b80b1186707b..000000000000
--- a/doc/release/next_whats_new/ttc_fonts.rst
+++ /dev/null
@@ -1,18 +0,0 @@
-Support for loading TrueType Collection fonts
----------------------------------------------
-
-TrueType Collection fonts (commonly found as files with a ``.ttc`` extension) are now
-supported. Namely, Matplotlib will include these file extensions in its scan for system
-fonts, and will add all sub-fonts to its list of available fonts (i.e., the list from
-`~.font_manager.get_font_names`).
-
-From most high-level API, this means you should be able to specify the name of any
-sub-font in a collection just as you would any other font. Note that at this time, there
-is no way to specify the entire collection with any sort of automated selection of the
-internal sub-fonts.
-
-In the low-level API, to ensure backwards-compatibility while facilitating this new
-support, a `.FontPath` instance (comprised of a font path and a sub-font index, with
-behaviour similar to a `str`) may be passed to the font management API in place of a
-simple `os.PathLike` path. Any font management API that previously returned a string path
-now returns a `.FontPath` instance instead.
diff --git a/doc/release/next_whats_new/twin_axes_zorder.rst b/doc/release/next_whats_new/twin_axes_zorder.rst
deleted file mode 100644
index 77ce9419fca0..000000000000
--- a/doc/release/next_whats_new/twin_axes_zorder.rst
+++ /dev/null
@@ -1,12 +0,0 @@
-Twin Axes ``delta_zorder``
---------------------------
-
-`~matplotlib.axes.Axes.twinx` and `~matplotlib.axes.Axes.twiny` now accept a
-*delta_zorder* keyword argument, a relative offset added to the original Axes'
-zorder, to control whether the twin Axes is drawn in front of, or behind, the
-original Axes.  For example, pass ``delta_zorder=-1`` to easily draw a twin Axes
-behind the main Axes.
-
-In addition, Matplotlib now automatically manages background patch visibility
-for each group of twinned Axes so that only the bottom-most Axes in the group
-has a visible background patch (respecting ``frameon``).
diff --git a/doc/release/next_whats_new/type1_subset.rst b/doc/release/next_whats_new/type1_subset.rst
deleted file mode 100644
index b0ab0a4337e6..000000000000
--- a/doc/release/next_whats_new/type1_subset.rst
+++ /dev/null
@@ -1,9 +0,0 @@
-PDF files created with usetex now embed subsets of Type 1 fonts
----------------------------------------------------------------
-
-When using the PDF backend with the usetex feature,
-Matplotlib calls TeX to render the text and formulas in the figure.
-The fonts that get used are usually "Type 1" fonts.
-They used to be embedded in full
-but are now limited to the glyphs that are actually used in the figure.
-This reduces the size of the resulting PDF files.
diff --git a/doc/release/next_whats_new/underline-23616.rst b/doc/release/next_whats_new/underline-23616.rst
deleted file mode 100644
index 184c588b842c..000000000000
--- a/doc/release/next_whats_new/underline-23616.rst
+++ /dev/null
@@ -1,12 +0,0 @@
-Underlining text while using Mathtext
--------------------------------------
-
-Mathtext now supports the ``\underline`` command.
-
-.. code-block:: python
-
-    import matplotlib.pyplot as plt
-
-    plt.text(0.4, 0.7, r'This is $\underline{underlined}$ text.')
-    plt.text(0.4, 0.3, r'So is $\underline{\mathrm{this}}$.')
-    plt.show()
diff --git a/doc/release/next_whats_new/updated_borderpad_parameter.rst b/doc/release/next_whats_new/updated_borderpad_parameter.rst
deleted file mode 100644
index 5acf075f7b51..000000000000
--- a/doc/release/next_whats_new/updated_borderpad_parameter.rst
+++ /dev/null
@@ -1,18 +0,0 @@
-``borderpad`` accepts a tuple for separate x/y padding
--------------------------------------------------------
-
-The ``borderpad`` parameter used for placing anchored artists (such as inset axes) now accepts a tuple of ``(x_pad, y_pad)``.
-
-This allows for specifying separate padding values for the horizontal and
-vertical directions, providing finer control over placement. For example, when
-placing an inset in a corner, one might want horizontal padding to avoid
-overlapping with the main plot's axis labels, but no vertical padding to keep
-the inset flush with the plot area edge.
-
-Example usage with :func:`~mpl_toolkits.axes_grid1.inset_locator.inset_axes`:
-
-.. code-block:: python
-
-    ax_inset = inset_axes(
-        ax, width="30%", height="30%", loc='upper left',
-        borderpad=(4, 0))
diff --git a/doc/release/next_whats_new/violin_stats.rst b/doc/release/next_whats_new/violin_stats.rst
deleted file mode 100644
index a764db01da59..000000000000
--- a/doc/release/next_whats_new/violin_stats.rst
+++ /dev/null
@@ -1,31 +0,0 @@
-``violin_stats`` simpler *method* parameter
--------------------------------------------
-
-The *method* parameter of `~.cbook.violin_stats` may now be specified as tuple of
-strings, and has a new default ``("GaussianKDE", "scott")``.  Calling
-`~.cbook.violin_stats` followed by `~.Axes.violin` is therefore now equivalent to
-calling `~.Axes.violinplot`.
-
-.. plot::
-    :include-source: true
-    :alt: Example showing violin_stats followed by violin gives the same result as violinplot
-
-    import matplotlib.pyplot as plt
-    from matplotlib.cbook import violin_stats
-    import numpy as np
-
-    rng = np.random.default_rng(19680801)
-    data = rng.normal(size=(10, 3))
-
-    fig, (ax1, ax2) = plt.subplots(ncols=2, layout='constrained', figsize=(6.4, 3.5))
-
-    # Create the violin plot in one step
-    ax1.violinplot(data)
-    ax1.set_title('One Step')
-
-    # Process the data and then create the violin plot
-    vstats = violin_stats(data)
-    ax2.violin(vstats)
-    ax2.set_title('Two Steps')
-
-    plt.show()
diff --git a/doc/release/next_whats_new/violinplot_colors.rst b/doc/release/next_whats_new/violinplot_colors.rst
deleted file mode 100644
index 179f868c4288..000000000000
--- a/doc/release/next_whats_new/violinplot_colors.rst
+++ /dev/null
@@ -1,8 +0,0 @@
-``violinplot`` now accepts color arguments
--------------------------------------------
-
-`~.Axes.violinplot` and `~.Axes.violin` now accept ``facecolor`` and
-``linecolor`` as input arguments. This means that users can set the color of
-violinplots as they make them, rather than setting the color of individual
-objects afterwards. It is possible to pass a single color to be used for all
-violins, or pass a sequence of colors.
diff --git a/doc/release/next_whats_new/webagg_capture_scroll.rst b/doc/release/next_whats_new/webagg_capture_scroll.rst
deleted file mode 100644
index 106e1ebdf36b..000000000000
--- a/doc/release/next_whats_new/webagg_capture_scroll.rst
+++ /dev/null
@@ -1,7 +0,0 @@
-WebAgg scroll capture control
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-The WebAgg backend now provides the ability to capture scroll events to prevent
-page scrolling when interacting with plots. This can be enabled or disabled via
-the new `.FigureCanvasWebAggCore.set_capture_scroll` and
-`.FigureCanvasWebAggCore.get_capture_scroll` methods.
diff --git a/doc/release/next_whats_new/xtick_ytick_rotation_modes.rst b/doc/release/next_whats_new/xtick_ytick_rotation_modes.rst
deleted file mode 100644
index 56286824ada5..000000000000
--- a/doc/release/next_whats_new/xtick_ytick_rotation_modes.rst
+++ /dev/null
@@ -1,28 +0,0 @@
-``xtick`` and ``ytick`` rotation modes
---------------------------------------
-
-A new feature has been added for handling rotation of xtick and ytick
-labels more intuitively. The new `rotation modes <matplotlib.text.Text.set_rotation_mode>`
-"xtick" and "ytick" automatically adjust the alignment of rotated tick labels,
-so that the text points towards their anchor point, i.e. ticks.  This works for
-all four sides of the plot (bottom, top, left, right), reducing the need for
-manual adjustments when rotating labels.
-
-.. plot::
-    :include-source: true
-    :alt: Example of rotated xtick and ytick labels.
-
-    import matplotlib.pyplot as plt
-
-    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7, 3.5), layout='constrained')
-
-    pos = range(5)
-    labels = ['label'] * 5
-    ax1.set_xticks(pos, labels, rotation=-45, rotation_mode='xtick')
-    ax1.set_yticks(pos, labels, rotation=45, rotation_mode='ytick')
-    ax2.xaxis.tick_top()
-    ax2.set_xticks(pos, labels, rotation=-45, rotation_mode='xtick')
-    ax2.yaxis.tick_right()
-    ax2.set_yticks(pos, labels, rotation=45, rotation_mode='ytick')
-
-    plt.show()
diff --git a/doc/release/next_whats_new/zoom_boxes.rst b/doc/release/next_whats_new/zoom_boxes.rst
deleted file mode 100644
index 8cc0cc1645a3..000000000000
--- a/doc/release/next_whats_new/zoom_boxes.rst
+++ /dev/null
@@ -1,4 +0,0 @@
-Consistent zoom boxes
----------------------
-
-Zooming now has a consistent dashed box style across all backends.
diff --git a/doc/release/prev_whats_new/whats_new_3.10.0.rst b/doc/release/prev_whats_new/whats_new_3.10.0.rst
index 232ab6036100..99889319da87 100644
--- a/doc/release/prev_whats_new/whats_new_3.10.0.rst
+++ b/doc/release/prev_whats_new/whats_new_3.10.0.rst
@@ -5,7 +5,7 @@ What's new in Matplotlib 3.10.0 (December 13, 2024)
 ===================================================
 
 For a list of all of the issues and pull requests since the last revision, see the
-:ref:`github-stats`.
+:ref:`github-stats-3_10_0`.
 
 .. contents:: Table of Contents
    :depth: 4
@@ -16,6 +16,8 @@ For a list of all of the issues and pull requests since the last revision, see t
 Accessible Colors
 =================
 
+.. _whats-new-3-10-0-petroff10:
+
 New more-accessible color cycle
 -------------------------------
 
diff --git a/doc/release/prev_whats_new/whats_new_3.11.0.rst b/doc/release/prev_whats_new/whats_new_3.11.0.rst
new file mode 100644
index 000000000000..973eedcda928
--- /dev/null
+++ b/doc/release/prev_whats_new/whats_new_3.11.0.rst
@@ -0,0 +1,1249 @@
+==============================================
+What's new in Matplotlib 3.11.0 (May 15, 2026)
+==============================================
+
+For a list of all of the issues and pull requests since the last revision, see the
+:ref:`github-stats`.
+
+.. contents:: Table of Contents
+   :depth: 4
+
+.. toctree::
+   :maxdepth: 4
+
+Figure creation / management
+============================
+
+Figures can be attached to and removed from pyplot
+--------------------------------------------------
+
+Figures can now be attached to and removed from management through pyplot, which in the
+background also means a less strict coupling to backends.
+
+In particular, standalone figures (created with the `.Figure` constructor) can now be
+registered with the `.pyplot` module by calling ``plt.figure(fig)``. This allows showing
+them with ``plt.show()`` as you would do with any figure created with pyplot factory
+functions such as ``plt.figure()`` or ``plt.subplots()``.
+
+When closing a shown figure window, the related figure is reset to the standalone state,
+i.e., it's not visible to pyplot anymore, but if you still hold a reference to it, you
+can continue to work with it (e.g. do ``fig.savefig()``, or re-add it to pyplot with
+``plt.figure(fig)`` and then show it again).
+
+The following is now possible - though the example is exaggerated to show what's
+possible. In practice, you'll stick with much simpler versions for better consistency ::
+
+    import matplotlib.pyplot as plt
+    from matplotlib.figure import Figure
+
+    # Create a standalone figure
+    fig = Figure()
+    ax = fig.add_subplot()
+    ax.plot([1, 2, 3], [4, 5, 6])
+
+    # Register it with pyplot
+    plt.figure(fig)
+
+    # Modify the figure through pyplot
+    plt.xlabel("x label")
+
+    # Show the figure
+    plt.show()
+
+    # Close the figure window through the GUI
+
+    # Continue to work on the figure
+    fig.savefig("my_figure.png")
+    ax.set_ylabel("y label")
+
+    # Re-register the figure and show it again
+    plt.figure(fig)
+    plt.show()
+
+.. dropdown:: Technical detail
+    :color: info
+    :icon: info
+
+    Standalone figures use `.FigureCanvasBase` as canvas. This is replaced by a
+    backend-dependent subclass when registering with pyplot, and is reset to
+    `.FigureCanvasBase` when the figure is closed. `.Figure.savefig` uses the current
+    canvas to save the figure (if possible). Since `.FigureCanvasBase` can not render
+    the figure, when saving the figure, it will fallback to a suitable canvas subclass,
+    e.g., `.FigureCanvasAgg` for raster outputs such as PNG.
+
+    Any Agg-based backend will create the same file output. However, there may be slight
+    differences for non-Agg backends; e.g. if you use "GTK4Cairo" as interactive
+    backend, ``fig.savefig("file.png")`` may create a slightly different image depending
+    on whether the figure is registered with pyplot or not.
+
+    In general, you should not store a reference to the canvas, but rather always obtain
+    it from the figure with ``fig.canvas``. This will return the current canvas, which
+    is either the original `.FigureCanvasBase` or a backend-dependent subclass,
+    depending on whether the figure is registered with pyplot or not.
+
+Figure size units
+-----------------
+
+When creating figures, it is now possible to define figure sizes in centimetres or
+pixels.
+
+Up to now the figure size is specified via ``plt.figure(..., figsize=(6, 4))``, and the
+given numbers are interpreted as inches. It is now possible to add a unit string to the
+tuple, i.e. ``plt.figure(..., figsize=(600, 400, "px"))``. Supported unit strings are
+``"in"``, ``"cm"``, or ``"px"``.
+
+Partial ``figsize`` specification at figure creation
+----------------------------------------------------
+
+Figure creation now accepts a single ``None`` in ``figsize``. Passing ``(None, h)`` uses
+the default width from :rc:`figure.figsize`, and passing ``(w, None)`` uses the default
+height. Passing ``(None, None)`` is invalid and raises a `ValueError`.
+
+For example::
+
+    plt.rcParams['figure.figsize'] = (14, 11)
+    fig = plt.figure(figsize=(None, 4))  # Size will be (14, 4)
+
+Subplot parameters are reset in ``Figure.clear``
+------------------------------------------------
+
+When calling `.Figure.clear()` the settings for `.gridspec.SubplotParams` are restored
+to the default values.
+
+`~.SubplotParams.to_dict` is a new method to get the subplot parameters as a dict, and
+`~.SubplotParams.reset` resets the parameters to the defaults.
+
+Plotting methods
+================
+
+Grouped bar charts
+------------------
+
+The new method `~.Axes.grouped_bar()` simplifies the creation of grouped bar charts
+significantly. It supports different input data types (lists of datasets, dicts of
+datasets, data in 2D arrays, pandas DataFrames), and allows for easy customization of
+placement via controllable distances between bars and between bar groups.
+
+.. plot::
+    :include-source:
+    :alt: Diagram of a grouped bar chart of 3 datasets with 2 categories.
+
+    categories = ['A', 'B']
+    datasets = {
+        'dataset 0': [1, 11],
+        'dataset 1': [3, 13],
+        'dataset 2': [5, 15],
+    }
+
+    fig, ax = plt.subplots()
+    ax.grouped_bar(datasets, tick_labels=categories)
+    ax.legend()
+
+``broken_barh()`` vertical alignment through *align* parameter
+--------------------------------------------------------------
+
+`~.Axes.broken_barh` now supports vertical alignment of the bars through the *align*
+parameter.
+
+``hist()`` supports a single color for multiple datasets
+--------------------------------------------------------
+
+It is now possible to pass a single *color* value to `~.Axes.hist()`. This value is
+applied to all datasets.
+
+Stackplot styling
+-----------------
+
+`~.Axes.stackplot` now accepts sequences for the style parameters *facecolor*,
+*edgecolor*, *linestyle*, and *linewidth*, similar to how the *hatch* parameter is
+already handled.
+
+Streamplot integration control
+------------------------------
+
+Two new options have been added to the `~.axes.Axes.streamplot` method that give better
+control of the streamline integration:
+
+``integration_max_step_scale``
+    Multiplies the default max step computed by the integrator.
+``integration_max_error_scale``
+    Multiplies the default max error set by the integrator.
+
+Values for these parameters between zero and one reduce (tighten) the max step or error
+to improve streamline accuracy by performing more computation. Values greater than one
+increase (loosen) the max step or error to reduce computation time at the cost of lower
+streamline accuracy.
+
+The integrator defaults are both hand-tuned values and may not be applicable to all
+cases, so this allows customizing the behavior to specific use cases. Modifying only
+``integration_max_step_scale`` has proved effective, but it may be useful to control the
+error as well.
+
+Multiple arrows on a streamline
+-------------------------------
+
+A new *num_arrows* argument has been added to `~matplotlib.axes.Axes.streamplot` that
+allows more than one arrow to be added to each streamline:
+
+.. plot::
+    :include-source:
+    :alt: One chart showing a streamplot. Each streamline has three arrows.
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+
+    w = 3
+    Y, X = np.mgrid[-w:w:100j, -w:w:100j]
+    U = -1 - X**2 + Y
+    V = 1 + X - Y**2
+
+    fig, ax = plt.subplots()
+    ax.streamplot(X, Y, U, V, num_arrows=3)
+
+    plt.show()
+
+``violinplot`` now accepts color arguments
+------------------------------------------
+
+`~.Axes.violinplot` and `~.Axes.violin` now accept ``facecolor`` and ``linecolor`` as
+input arguments. This means that the color of violinplots can be set as they are made,
+rather than setting the color of individual objects afterwards. It is possible to pass a
+single color to be used for all violins, or pass a sequence of colors.
+
+Annotations
+===========
+
+``bar_label`` supports individual padding per label
+---------------------------------------------------
+
+`~.Axes.bar_label` will now accept both a float value or an array-like for padding. The
+array-like defines the padding for each label individually.
+
+Adding labels to pie chart wedges
+---------------------------------
+
+The new `~.Axes.pie_label` method adds a label to each wedge in a pie chart created with
+`~.Axes.pie`.  It can take
+
+* a list of strings, similar to the existing *labels* parameter of `~.Axes.pie`
+* a format string similar to the existing *autopct* parameter of `~.Axes.pie` except
+  that it uses the `str.format` method and it can handle absolute values as well as
+  fractions/percentages
+
+For more examples, see :doc:`/gallery/pie_and_polar_charts/pie_label`.
+
+.. plot::
+    :include-source:
+    :alt:
+        A pie chart with three labels on each wedge, showing a food type, number, and
+        fraction associated with the wedge.
+
+    import matplotlib.pyplot as plt
+
+    data = [36, 24, 8, 12]
+    labels = ['spam', 'eggs', 'bacon', 'sausage']
+
+    fig, ax = plt.subplots()
+    pie = ax.pie(data)
+
+    ax.pie_label(pie, labels, distance=1.1)
+    ax.pie_label(pie, '{frac:.1%}', distance=0.7)
+    ax.pie_label(pie, '{absval:d}', distance=0.4)
+
+Arrow-style sub-classes of ``BoxStyle`` support arrow head resizing
+-------------------------------------------------------------------
+
+The new *head_width* and *head_angle* parameters to `.BoxStyle.LArrow`,
+`.BoxStyle.RArrow` and `.BoxStyle.DArrow` allow for adjustment of the size and aspect
+ratio of the arrow heads used.
+
+To give a consistent appearance across all parameter values, the default head position
+(where the head starts relative to text) is slightly changed compared to the previous
+hard-coded position.
+
+By using negative angles (or corresponding reflex angles) for *head_angle*, arrows with
+'backwards' heads may be created.
+
+.. plot::
+    :include-source:
+    :alt:
+        Six arrow-shaped text boxes.  The arrows on the left have the shaft on their
+        left; the arrows on the right have the shaft on the right; the arrows in the
+        middle have shafts on both sides.
+
+    import matplotlib.pyplot as plt
+
+    plt.text(0.2, 0.8, "LArrow", ha='center', size=16,
+             bbox=dict(boxstyle="larrow, pad=0.3, head_angle=150"))
+    plt.text(0.2, 0.2, "LArrow", ha='center', size=16,
+             bbox=dict(boxstyle="larrow, pad=0.3, head_width=0.5"))
+    plt.text(0.5, 0.8, "DArrow", ha='center', size=16,
+             bbox=dict(boxstyle="darrow, pad=0.3, head_width=3"))
+    plt.text(0.5, 0.2, "DArrow", ha='center', size=16,
+             bbox=dict(boxstyle="darrow, pad=0.3, head_width=1, head_angle=60"))
+    plt.text(0.8, 0.8, "RArrow", ha='center', size=16,
+             bbox=dict(boxstyle="rarrow, pad=0.3, head_angle=30"))
+    plt.text(0.8, 0.2, "RArrow", ha='center', size=16,
+             bbox=dict(boxstyle="rarrow, pad=0.3, head_width=2, head_angle=-90"))
+
+    plt.show()
+
+*borderpad* accepts a tuple for separate x/y padding
+----------------------------------------------------
+
+The *borderpad* parameter used for placing anchored artists (such as inset axes) now
+accepts a tuple of ``(x_pad, y_pad)``.
+
+This allows for specifying separate padding values for the horizontal and vertical
+directions, providing finer control over placement. For example, when placing an inset
+in a corner, one might want horizontal padding to avoid overlapping with the main plot's
+axis labels, but no vertical padding to keep the inset flush with the plot area edge.
+
+Example usage with :func:`~mpl_toolkits.axes_grid1.inset_locator.inset_axes`:
+
+.. code-block:: python
+
+    ax_inset = inset_axes(
+        ax, width="30%", height="30%", loc='upper left',
+        borderpad=(4, 0))
+
+Axes and Artists
+================
+
+Twin Axes ``delta_zorder``
+--------------------------
+
+`~matplotlib.axes.Axes.twinx` and `~matplotlib.axes.Axes.twiny` now accept a
+*delta_zorder* keyword argument, a relative offset added to the original Axes' zorder,
+to control whether the twin Axes is drawn in front of, or behind, the original Axes. For
+example, pass ``delta_zorder=-1`` to draw a twin Axes behind the main Axes.
+
+In addition, Matplotlib now automatically manages background patch visibility for each
+group of twinned Axes so that only the bottom-most Axes in the group has a visible
+background patch (respecting ``frameon``).
+
+``BarContainer`` properties
+---------------------------
+
+`.BarContainer` gained new properties to easily access coordinates of the bars:
+
+- `~.BarContainer.bottoms`
+- `~.BarContainer.tops`
+- `~.BarContainer.position_centers`
+
+Maximum levels on log-scaled contour plots are now respected
+------------------------------------------------------------
+
+When plotting contours with a log norm, passing an integer value to the ``levels``
+argument to cap the maximum number of contour levels now works as intended.
+
+``edgegapcolor`` for Patches
+----------------------------
+
+`~matplotlib.patches.Patch` now supports an *edgegapcolor* parameter, similar to the
+existing *gapcolor* in `.Line2D`. This allows patches with dashed edges to display a
+secondary color in the gaps, creating a "striped" edge effect.
+
+This is useful when drawing unfilled patches on backgrounds of unknown color, where
+alternating edge colors ensure the patch boundary remains visible.
+
+.. plot::
+    :include-source:
+    :alt:
+        A rectangle with a dashed orange edge and blue gaps, demonstrating the
+        edgegapcolor feature.
+
+    import matplotlib.pyplot as plt
+    from matplotlib.patches import Rectangle
+
+    fig, ax = plt.subplots()
+    rect = Rectangle((0.1, 0.1), 0.6, 0.6, fill=False,
+                      edgecolor='orange', edgegapcolor='blue',
+                      linestyle='--', linewidth=3)
+    ax.add_patch(rect)
+    plt.show()
+
+Separated ``hatchcolor`` from ``edgecolor``
+-------------------------------------------
+
+When the *hatchcolor* parameter is specified, it will be used for the hatch. If it is
+not specified, it will fall back to using :rc:`hatch.color`. The special value 'edge'
+uses the patch edgecolor, with a fallback to :rc:`patch.edgecolor` if the patch
+edgecolor is 'none'. Previously, hatch colors were the same as edge colors, with a
+fallback to :rc:`hatch.color` if the patch did not have an edge color.
+
+.. plot::
+    :include-source:
+    :alt:
+        Four Rectangle patches, each displaying the color of hatches in different
+        specifications of edgecolor and hatchcolor. Top left has hatchcolor='black'
+        representing the default value when both hatchcolor and edgecolor are not set,
+        top right has edgecolor='blue' and hatchcolor='black' which remains when the
+        edgecolor is set again, bottom left has edgecolor='red' and hatchcolor='orange'
+        on explicit specification and bottom right has edgecolor='green' and
+        hatchcolor='green' when the hatchcolor is not set.
+
+    import matplotlib as mpl
+    import matplotlib.pyplot as plt
+    from matplotlib.patches import Rectangle
+
+    fig, ax = plt.subplots()
+
+    # In this case, hatchcolor is orange
+    patch1 = Rectangle((0.1, 0.1), 0.3, 0.3, edgecolor='red', linewidth=2,
+                       hatch='//', hatchcolor='orange')
+    ax.add_patch(patch1)
+
+    # When hatchcolor is not specified, it matches edgecolor
+    # In this case, hatchcolor is green
+    patch2 = Rectangle((0.6, 0.1), 0.3, 0.3, edgecolor='green', linewidth=2,
+                       hatch='//', facecolor='none')
+    ax.add_patch(patch2)
+
+    # If both hatchcolor and edgecolor are not specified
+    # it will default to the 'patch.edgecolor' rcParam, which is black by default
+    # In this case, hatchcolor is black
+    patch3 = Rectangle((0.1, 0.6), 0.3, 0.3, hatch='//')
+    ax.add_patch(patch3)
+
+    # When using `hatch.color` in the `rcParams`
+    # edgecolor will now not overwrite hatchcolor
+    # In this case, hatchcolor is black
+    with plt.rc_context({'hatch.color': 'black'}):
+        patch4 = Rectangle((0.6, 0.6), 0.3, 0.3, edgecolor='blue', linewidth=2,
+                           hatch='//', facecolor='none')
+
+    # hatchcolor is black (it uses the `hatch.color` rcParam value)
+    patch4.set_edgecolor('blue')
+    # hatchcolor is still black (here, it does not update when edgecolor changes)
+    ax.add_patch(patch4)
+
+    ax.annotate("hatchcolor = 'orange'",
+                xy=(.5, 1.03), xycoords=patch1, ha='center', va='bottom')
+    ax.annotate("hatch color unspecified\nedgecolor='green'",
+                xy=(.5, 1.03), xycoords=patch2, ha='center', va='bottom')
+    ax.annotate("hatch color unspecified\nusing patch.edgecolor",
+                xy=(.5, 1.03), xycoords=patch3, ha='center', va='bottom')
+    ax.annotate("hatch.color='black'",
+                xy=(.5, 1.03), xycoords=patch4, ha='center', va='bottom')
+
+    plt.show()
+
+For collections, a sequence of colors can be passed to the *hatchcolor* parameter which
+will be cycled through for each hatch, similar to *facecolor* and *edgecolor*.
+
+Previously, if *edgecolor* was not specified, the hatch color would fall back to
+:rc:`patch.edgecolor`, but the alpha value would default to **1.0**, regardless of the
+alpha value of the collection. This behavior has been changed such that, if both
+*hatchcolor* and *edgecolor* are not specified, the hatch color will fall back to
+'patch.edgecolor' with the alpha value of the collection.
+
+.. plot::
+    :include-source:
+    :alt:
+        A random scatter plot with hatches on the markers. The hatches are colored in
+        blue, orange, and green, respectively. After the first three markers, the colors
+        are cycled through again.
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+
+    np.random.seed(19680801)
+
+    fig, ax = plt.subplots()
+
+    x = [29, 36, 41, 25, 32, 70, 62, 58, 66, 80, 58, 68, 62, 37, 48]
+    y = [82, 76, 48, 53, 62, 70, 84, 68, 55, 75, 29, 25, 12, 17, 20]
+    colors = ['tab:blue'] * 5 + ['tab:orange'] * 5 + ['tab:green'] * 5
+
+    ax.scatter(
+        x,
+        y,
+        s=800,
+        hatch="xxxx",
+        hatchcolor=colors,
+        facecolor="none",
+        edgecolor="black",
+    )
+
+    plt.show()
+
+Axis and Ticks
+==============
+
+Standard getters/setters for axis inversion state
+-------------------------------------------------
+
+Whether an axis is inverted can now be queried using the `.axes.Axes` getters
+`~.Axes.get_xinverted`/`~.Axes.get_yinverted` and set using
+`~.Axes.set_xinverted`/`~.Axes.set_yinverted`.
+
+The previously existing methods (`.Axes.xaxis_inverted`, `.Axes.invert_xaxis`) are now
+discouraged (but not deprecated) due to their non-standard naming and behavior.
+
+``xtick`` and ``ytick`` rotation modes
+--------------------------------------
+
+A new feature has been added for handling rotation of xtick and ytick labels more
+intuitively. The new `rotation modes <matplotlib.text.Text.set_rotation_mode>` "xtick"
+and "ytick" automatically adjust the alignment of rotated tick labels, so that the text
+points towards their anchor point, i.e. ticks. This works for all four sides of the plot
+(bottom, top, left, right), reducing the need for manual adjustments when rotating
+labels.
+
+.. plot::
+    :include-source:
+    :alt: Example of rotated xtick and ytick labels.
+
+    import matplotlib.pyplot as plt
+
+    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7, 3.5), layout='constrained')
+
+    pos = range(5)
+    labels = ['label'] * 5
+    ax1.set_xticks(pos, labels, rotation=-45, rotation_mode='xtick')
+    ax1.set_yticks(pos, labels, rotation=45, rotation_mode='ytick')
+    ax2.xaxis.tick_top()
+    ax2.set_xticks(pos, labels, rotation=-45, rotation_mode='xtick')
+    ax2.yaxis.tick_right()
+    ax2.set_yticks(pos, labels, rotation=45, rotation_mode='ytick')
+
+    plt.show()
+
+Improved selection of log-scale ticks
+-------------------------------------
+
+The algorithm for selecting log-scale ticks (on powers of ten) has been improved. In
+particular, it will now always draw as many ticks as possible (e.g., it will not draw a
+single tick if it was possible to fit two ticks); if subsampling ticks, it will prefer
+putting ticks on integer multiples of the subsampling stride (e.g., it prefers putting
+ticks at 10\ :sup:`0`, 10\ :sup:`3`, 10\ :sup:`6` rather than 10\ :sup:`1`, 10\
+:sup:`4`, 10\ :sup:`7`) if this results in the same number of ticks at the end; and it
+is now more robust against floating-point calculation errors.
+
+Colors and colormaps
+====================
+
+Okabe-Ito accessible color sequence
+-----------------------------------
+
+Matplotlib now includes the `Okabe-Ito color sequence
+<https://jfly.uni-koeln.de/color/#pallet>`_. Its colors remain distinguishable for
+common forms of color-vision deficiency and when printed.
+
+For example, to set it as the default colormap for your plots and image-like artists,
+use:
+
+.. code-block:: python
+
+    import matplotlib.pyplot as plt
+    from cycler import cycler
+
+    plt.rcParams['axes.prop_cycle'] = cycler(color='okabe_ito')
+    plt.rcParams['image.cmap'] = 'okabe_ito'
+
+Or, when creating plots, you can pass it explicitly:
+
+.. plot::
+
+    import matplotlib.pyplot as plt
+
+    colors = plt.colormaps['okabe_ito'].colors
+    x = range(5)
+    for i, c in enumerate(colors):
+        plt.plot(x, [v*(i+1) for v in x], color=c, label=f'line {i}')
+    plt.legend()
+    plt.show()
+
+Six and eight color Petroff color cycles
+----------------------------------------
+
+The six and eight color accessible Petroff color cycles are named ``'petroff6'`` and
+``'petroff8'``. They complement the existing ``'petroff10'`` color cycle, added in
+:ref:`Matplotlib 3.10.0 <whats-new-3-10-0-petroff10>`.
+
+For more details see `Petroff, M. A.: "Accessible Color Sequences for Data
+Visualization" <https://arxiv.org/abs/2107.02270>`_. To load the ``'petroff6'`` color
+cycle in place of the default::
+
+  import matplotlib.pyplot as plt
+  plt.style.use('petroff6')
+
+or to load the ``'petroff8'`` color cycle::
+
+  import matplotlib.pyplot as plt
+  plt.style.use('petroff8')
+
+Setting the default color cycle to a named color sequence
+---------------------------------------------------------
+
+The default color cycle may now be configured in the ``matplotlibrc`` file or a style
+file to use any of the :doc:`/gallery/color/color_sequences`. For example
+
+.. code-block:: none
+
+   axes.prop_cycle : cycler(color='Accent')
+
+Colormaps support giving colors for bad, under and over values on creation
+--------------------------------------------------------------------------
+
+Colormaps gained keyword arguments ``bad``, ``under``, and ``over`` to specify these
+values on creation. Previously, these values would have to be set afterwards using one
+of `~.Colormap.set_bad`, `~.Colormap.set_under`, `~.Colormap.set_bad`,
+`~.Colormap.set_extremes`, `~.Colormap.with_extremes`.
+
+It is recommended to use the new functionality, e.g.::
+
+    cmap = ListedColormap(colors, bad="red", under="darkblue", over="purple")
+
+instead of::
+
+    cmap = ListedColormap(colors).with_extremes(
+        bad="red", under="darkblue", over="purple")
+
+or::
+
+   cmap = ListedColormap(colors)
+   cmap.set_bad("red")
+   cmap.set_under("darkblue")
+   cmap.set_over("purple")
+
+Tuning transparency of colormaps
+--------------------------------
+
+The new method `.Colormap.with_alpha` allows to create a new colormap with the same
+color values but a new uniform alpha value. This is handy if you want to modify only the
+transparency of mapped colors for an Artist.
+
+Fonts and Text
+==============
+
+Complex text layout with libraqm
+--------------------------------
+
+Text support has been extended to include complex text layout. This support includes:
+
+1. Languages that require advanced layout, such as Arabic or Hebrew.
+2. Text that mixes left-to-right and right-to-left languages.
+
+   .. plot::
+       :show-source-link: False
+
+       text = 'Here is some رَقْم in اَلْعَرَبِيَّةُ'
+       fig = plt.figure(figsize=(6, 1))
+       fig.text(0.5, 0.5, text, size=32, ha='center', va='center')
+
+3. Ligatures that combine several adjacent characters for improved legibility.
+
+   .. plot::
+       :show-source-link: False
+
+       text = 'f\N{Hair Space}f\N{Hair Space}i \N{Rightwards Arrow} ffi'
+       fig = plt.figure(figsize=(3, 1))
+       fig.text(0.5, 0.5, text, size=32, ha='center', va='center')
+
+4. Combining multiple or double-width diacritics.
+
+   .. plot::
+       :show-source-link: False
+
+       text = (
+           'a\N{Combining Circumflex Accent}\N{Combining Double Tilde}'
+           'c\N{Combining Diaeresis}')
+       text = ' + '.join(
+           c if c in 'ac' else f'\N{Dotted Circle}{c}'
+           for c in text) + f' \N{Rightwards Arrow} {text}'
+       fig = plt.figure(figsize=(6, 1))
+       fig.text(0.5, 0.5, text, size=32, ha='center', va='center',
+                # Builtin DejaVu Sans doesn't support multiple diacritics.
+                family=['Noto Sans', 'DejaVu Sans'])
+
+Note, all advanced features require corresponding font support, and may require
+additional fonts over the builtin DejaVu Sans.
+
+Specifying font feature tags
+----------------------------
+
+OpenType fonts may support feature tags that specify alternate glyph shapes or
+substitutions to be made optionally. The text API now supports setting a list of feature
+tags to be used with the associated font. Feature tags can be set/get with:
+
+- `matplotlib.text.Text.set_fontfeatures` / `matplotlib.text.Text.get_fontfeatures`
+- Any API that creates a `.Text` object by passing the *fontfeatures* argument (e.g.,
+  ``plt.xlabel(..., fontfeatures=...)``)
+
+Font feature strings are eventually passed to HarfBuzz, and so all `string formats
+supported by hb_feature_from_string()
+<https://harfbuzz.github.io/harfbuzz-hb-common.html#hb-feature-from-string>`__ are
+supported. Note though that subranges are not explicitly supported and behaviour may
+change in the future.
+
+For example, the default font ``DejaVu Sans`` enables Standard Ligatures (the ``'liga'``
+tag) by default, and also provides optional Discretionary Ligatures (the ``dlig`` tag.)
+These may be toggled with ``+`` or ``-``.
+
+.. plot::
+    :include-source:
+
+    fig = plt.figure(figsize=(7, 3))
+
+    fig.text(0.5, 0.85, 'Ligatures', fontsize=40, horizontalalignment='center')
+
+    # Default has Standard Ligatures (liga).
+    fig.text(0, 0.6, 'Default: fi ffi fl st', fontsize=40)
+
+    # Disable Standard Ligatures with -liga.
+    fig.text(0, 0.35, 'Disabled: fi ffi fl st', fontsize=40,
+             fontfeatures=['-liga'])
+
+    # Enable Discretionary Ligatures with dlig.
+    fig.text(0, 0.1, 'Discretionary: fi ffi fl st', fontsize=40,
+             fontfeatures=['dlig'])
+
+Available font feature tags may be found at
+https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist
+
+Specifying text language
+------------------------
+
+OpenType fonts may support language systems which can be used to select different
+typographic conventions, e.g., localized variants of letters that share a single Unicode
+code point, or different default font features. The text API now supports setting a
+language to be used and may be set/get with:
+
+- `matplotlib.text.Text.set_language` / `matplotlib.text.Text.get_language`
+- Any API that creates a `.Text` object by passing the *language* argument (e.g.,
+  ``plt.xlabel(..., language=...)``)
+
+The language of the text must be in a format accepted by libraqm, namely `a BCP47
+language code <https://www.w3.org/International/articles/language-tags/>`_. If None or
+unset, then no particular language will be implied, and default font settings will be
+used.
+
+For example, Matplotlib's default font ``DejaVu Sans`` supports language-specific glyphs
+in the Serbian and Macedonian languages in the Cyrillic alphabet (vs Russian), or the
+Sámi family of languages in the Latin alphabet (vs English).
+
+.. plot::
+    :include-source:
+
+    fig = plt.figure(figsize=(7, 3))
+
+    char = '\U00000431'
+    fig.text(0.5, 0.8, f'\\U{ord(char):08x}', fontsize=40, horizontalalignment='center')
+    fig.text(0, 0.6, f'Serbian: {char}', fontsize=40, language='sr')
+    fig.text(1, 0.6, f'Russian: {char}', fontsize=40, language='ru',
+             horizontalalignment='right')
+
+    char = '\U0000014a'
+    fig.text(0.5, 0.3, f'\\U{ord(char):08x}', fontsize=40, horizontalalignment='center')
+    fig.text(0, 0.1, f'Inari Sámi: {char}', fontsize=40, language='smn')
+    fig.text(1, 0.1, f'English: {char}', fontsize=40, language='en',
+             horizontalalignment='right')
+
+Missing glyphs use Last Resort font
+-----------------------------------
+
+Most fonts do not have 100% character coverage, and will fall back to a "not found"
+glyph for characters that are not provided. Often, this glyph will be minimal (e.g., the
+default DejaVu Sans "not found" glyph is just a rectangle.) Such minimal glyphs provide
+no context as to the characters that are missing.
+
+Now, missing glyphs will fall back to the `Last Resort font
+<https://github.com/unicode-org/last-resort-font>`__ produced by the Unicode Consortium.
+This special-purpose font provides glyphs that represent types of Unicode characters.
+These glyphs show a representative character from the missing Unicode block, and at
+larger sizes, more context to help determine which character and font are needed.
+
+To disable this fallback behaviour, set :rc:`font.enable_last_resort` to ``False``.
+
+.. plot::
+    :alt:
+        An example of missing glyph behaviour, the first glyph from Bengali script,
+        second glyph from Hiragana, and the last glyph from the Unicode Private Use
+        Area. Multiple lines repeat the text with increasing font size from top to
+        bottom.
+
+    text_raw = r"'\N{Bengali Digit Zero}\N{Hiragana Letter A}\ufdd0'"
+    text = eval(text_raw)
+    sizes = [
+        (0.85, 8),
+        (0.80, 10),
+        (0.75, 12),
+        (0.70, 16),
+        (0.63, 20),
+        (0.55, 24),
+        (0.45, 32),
+        (0.30, 48),
+        (0.10, 64),
+    ]
+
+    fig = plt.figure()
+    fig.text(0.01, 0.90, f'Input: {text_raw}')
+    for y, size in sizes:
+        fig.text(0.01, y, f'{size}pt:{text}', fontsize=size)
+
+Fonts addressable by all their SFNT family names
+------------------------------------------------
+
+Fonts can now be selected by any of the family names they advertise in the OpenType name
+table, not just the one FreeType reports as the primary family name.
+
+Some fonts store different family names on different platforms or in different
+name-table entries.  For example, Ubuntu Light stores ``"Ubuntu"`` in the
+Macintosh-platform Name ID 1 slot (which FreeType uses as the primary name) and
+``"Ubuntu Light"`` in the Microsoft-platform Name ID 1 slot.  Previously only the
+FreeType-derived name was registered, requiring an obscure weight-based workaround::
+
+    # Previously required
+    matplotlib.rcParams['font.family'] = 'Ubuntu'
+    matplotlib.rcParams['font.weight'] = 300
+
+All name-table entries that describe a family — Name ID 1 on both platforms, the
+Typographic Family (Name ID 16), and the WWS Family (Name ID 21) — are now registered as
+separate entries in the `~matplotlib.font_manager.FontManager`, so any of those names
+can be used directly::
+
+    matplotlib.rcParams['font.family'] = 'Ubuntu Light'
+
+Support for loading TrueType Collection fonts
+---------------------------------------------
+
+TrueType Collection fonts (commonly found as files with a ``.ttc`` extension) are now
+supported. Namely, Matplotlib will include these file extensions in its scan for system
+fonts, and will add all sub-fonts to its list of available fonts (i.e., the list from
+`~.font_manager.get_font_names`).
+
+From most high-level API, this means you should be able to specify the name of any
+sub-font in a collection just as you would any other font. Note that at this time, there
+is no way to specify the entire collection with any sort of automated selection of the
+internal sub-fonts.
+
+In the low-level API, to ensure backwards-compatibility while facilitating this new
+support, a `.FontPath` instance (comprised of a font path and a sub-font index, with
+behaviour similar to a `str`) may be passed to the font management API in place of a
+simple `os.PathLike` path. Any font management API that previously returned a string
+path now returns a `.FontPath` instance instead.
+
+New environment variable to ignore system fonts
+-----------------------------------------------
+
+System fonts may be ignored by setting the :envvar:`MPL_IGNORE_SYSTEM_FONTS`; this
+suppresses searching for system fonts (in known directories or via some
+platform-specific subprocess) as well as limiting the results from
+`.FontManager.findfont`.
+
+Mathtext distinguishes *italic* and *normal* font
+-------------------------------------------------
+
+Matplotlib's lightweight TeX expression parser (``usetex=False``) now distinguishes
+between *italic* and *normal* math fonts to closer replicate the behaviour of LaTeX. The
+normal math font is selected by default in math environment (unless the rcParam
+``mathtext.default`` is overwritten) but can be explicitly set with the new
+``\mathnormal`` command. Italic font is selected with ``\mathit``. The main difference
+is that *italic* produces italic digits, whereas *normal* produces upright digits.
+Previously, it was not possible to typeset italic digits. Note that ``normal`` now
+corresponds to what used to be ``it``, whereas ``it`` now renders all characters italic.
+**Important**: In case the default mathematics font is overwritten by setting
+``mathtext.default: it`` in ``matplotlibrc``, it must be either commented out or changed
+to ``mathtext.default: normal`` to preserve its behaviour. Otherwise, all alphanumeric
+characters, including digits, are rendered italic.
+
+One difference to traditional LaTeX is that LaTeX further distinguishes between *normal*
+(``\mathnormal``) and *default math*, where the default uses roman digits and normal
+uses oldstyle digits. This distinction is no longer present with modern LaTeX engines
+and unicode-math nor in Matplotlib.
+
+mathtext support for ``\phantom``, ``\llap``, ``\rlap``
+-------------------------------------------------------
+
+mathtext gained support for the TeX macros ``\phantom``, ``\llap``, and ``\rlap``.
+``\phantom`` allows to occupy some space on the canvas as if some text was being
+rendered, without actually rendering that text, whereas ``\llap`` and ``\rlap`` allows
+to render some text on the canvas while pretending that it occupies no space.
+Altogether these macros allow some finer control of text alignments.
+
+See https://www.tug.org/TUGboat/tb22-4/tb72perlS.pdf for a detailed description of these
+macros.
+
+Underlining text while using Mathtext
+-------------------------------------
+
+Mathtext now supports the ``\underline`` command.
+
+.. code-block:: python
+
+    import matplotlib.pyplot as plt
+
+    plt.text(0.4, 0.7, r'This is $\underline{underlined}$ text.')
+    plt.text(0.4, 0.3, r'So is $\underline{\mathrm{this}}$.')
+    plt.show()
+
+Improved font embedding in PDF
+------------------------------
+
+Both Type 3 and Type 42 fonts (see :ref:`fonts` for more details) are now embedded into
+PDFs without limitation. Fonts may be split into multiple embedded subsets in order to
+satisfy format limits. Additionally, a corrected Unicode mapping is added for each.
+
+This means that *all* text should now be selectable and copyable in PDF viewers that
+support doing so.
+
+When using the ``usetex`` feature, Matplotlib calls TeX to render the text and formulas
+in the figure. The fonts that get used are usually "Type 1" fonts. They used to be
+embedded in full but are now limited to the glyphs that are actually used in the figure.
+This reduces the size of the resulting PDF files.
+
+rcParams improvements
+=====================
+
+Separate styling options for major/minor grid line in rcParams
+--------------------------------------------------------------
+
+Using :rc:`grid.major.*` or :rc:`grid.minor.*` will overwrite the value in :rc:`grid.*`
+for the major and minor gridlines, respectively.
+
+.. plot::
+    :include-source:
+    :alt: Modifying the gridlines using the new options `rcParams`
+
+    import matplotlib as mpl
+    import matplotlib.pyplot as plt
+
+
+    # Set visibility for major and minor gridlines
+    mpl.rcParams["axes.grid"] = True
+    mpl.rcParams["ytick.minor.visible"] = True
+    mpl.rcParams["xtick.minor.visible"] = True
+    mpl.rcParams["axes.grid.which"] = "both"
+
+    # Using old values to set both major and minor properties
+    mpl.rcParams["grid.color"] = "red"
+    mpl.rcParams["grid.linewidth"] = 1
+
+    # Overwrite some values for major and minor separately
+    mpl.rcParams["grid.major.color"] = "black"
+    mpl.rcParams["grid.major.linewidth"] = 2
+    mpl.rcParams["grid.minor.linestyle"] = ":"
+    mpl.rcParams["grid.minor.alpha"] = 0.6
+
+    plt.plot([0, 1], [0, 1])
+
+    plt.show()
+
+``axes.prop_cycle`` rcParam security improvements
+-------------------------------------------------
+
+The ``axes.prop_cycle`` rcParam is now parsed in a safer and more restricted manner.
+Only literals, ``cycler()`` and ``concat()`` calls, the operators ``+`` and ``*``, and
+slicing are allowed. All previously valid cycler strings documented at
+https://matplotlib.org/cycler/ are still supported, for example:
+
+.. code-block:: none
+
+   axes.prop_cycle : cycler('color', ['r', 'g', 'b']) + cycler('linewidth', [1, 2, 3])
+   axes.prop_cycle : 2 * cycler('color', 'rgb')
+   axes.prop_cycle : concat(cycler('color', 'rgb'), cycler('color', 'cmk'))
+   axes.prop_cycle : cycler('color', 'rgbcmk')[:3]
+
+Legends
+=======
+
+``legend.linewidth`` rcParam and parameter
+------------------------------------------
+
+A new rcParam ``legend.linewidth`` has been added to control the line width of the
+legend's box edges. When set to ``None`` (the default), it inherits the value from
+``patch.linewidth``. This allows for independent control of the legend frame line width
+without affecting other elements.
+
+The `.Legend` constructor also accepts a new *linewidth* parameter to set the legend
+frame line width directly, overriding the rcParam value.
+
+.. plot::
+    :include-source:
+    :alt: A line plot with a legend showing a thick border around the legend box.
+
+    import matplotlib.pyplot as plt
+
+    fig, ax = plt.subplots()
+    ax.plot([1, 2, 3], label='data')
+    ax.legend(linewidth=2.0)  # Thick legend box edge
+    plt.show()
+
+``PatchCollection`` legends now supported
+-----------------------------------------
+
+`.PatchCollection` instances now properly display in legends when given a label.
+Previously, labels on `~.PatchCollection` objects were ignored by the legend system,
+requiring users to create manual legend entries.
+
+.. plot::
+   :include-source:
+   :alt:
+       The legend entry displays a rectangle matching the visual properties (colors,
+       line styles, line widths) of the first patch in the collection.
+
+    import matplotlib.pyplot as plt
+    import matplotlib.patches as mpatches
+    from matplotlib.collections import PatchCollection
+
+    fig, ax = plt.subplots()
+    patches = [mpatches.Circle((0, 0), 0.1), mpatches.Rectangle((0.5, 0.5), 0.2, 0.3)]
+    pc = PatchCollection(patches, facecolor='blue', edgecolor='black', label='My patches')
+    ax.add_collection(pc)
+    ax.legend()  # Now displays the label "My patches"
+    plt.show()
+
+Widgets and Interactivity
+=========================
+
+Zooming using mouse wheel
+-------------------------
+
+:kbd:`Control+MouseWheel` can be used to zoom in the plot windows. Additionally,
+:kbd:`x+MouseWheel` zooms only the x-axis and :kbd:`y+MouseWheel` zooms only the y-axis.
+
+The zoom focusses on the mouse pointer. With :kbd:`Control`, the axes aspect ratio is
+kept; with :kbd:`x` or :kbd:`y`, only the respective axis is scaled.
+
+Zooming is currently only supported on rectilinear Axes.
+
+Consistent zoom boxes
+---------------------
+
+Zooming now has a consistent dashed box style across all backends.
+
+RadioButtons and CheckButtons widgets support flexible layouts
+--------------------------------------------------------------
+
+The `.widgets.RadioButtons` and `.widgets.CheckButtons` widgets now support arranging
+buttons in different layouts via the new *layout* parameter. You can arrange buttons
+vertically (default), horizontally, or in a 2D grid by passing a ``(rows, cols)`` tuple.
+
+See :doc:`/gallery/widgets/radio_buttons_grid` for a ``(rows, cols)`` example.
+
+.. plot::
+    :include-source:
+    :alt: Multiple sine waves with checkboxes to toggle their visibility.
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+    from matplotlib.widgets import CheckButtons
+
+    t = np.arange(0.0, 2.0, 0.01)
+    s0 = np.sin(2*np.pi*t)
+    s1 = np.sin(4*np.pi*t)
+    s2 = np.sin(6*np.pi*t)
+    s3 = np.sin(8*np.pi*t)
+
+    fig, axes = plt.subplot_mosaic(
+        [['main'], ['buttons']],
+        height_ratios=[8, 1],
+        layout="constrained",
+    )
+
+    l0, = axes['main'].plot(t, s0, lw=2, color='red', label='2 Hz')
+    l1, = axes['main'].plot(t, s1, lw=2, color='green', label='4 Hz')
+    l2, = axes['main'].plot(t, s2, lw=2, color='blue', label='6 Hz')
+    l3, = axes['main'].plot(t, s3, lw=2, color='purple', label='8 Hz')
+    axes['main'].set_xlabel('Time (s)')
+    axes['main'].set_ylabel('Amplitude')
+
+    lines_by_label = {l.get_label(): l for l in [l0, l1, l2, l3]}
+
+    axes['buttons'].set_facecolor('0.9')
+    check = CheckButtons(
+        axes['buttons'],
+        labels=lines_by_label.keys(),
+        actives=[l.get_visible() for l in lines_by_label.values()],
+        layout='horizontal'
+    )
+
+    def callback(label):
+        ln = lines_by_label[label]
+        ln.set_visible(not ln.get_visible())
+        fig.canvas.draw_idle()
+
+    check.on_clicked(callback)
+    plt.show()
+
+Callable *valfmt* for ``Slider`` and ``RangeSlider``
+----------------------------------------------------
+
+In addition to the existing %-format string, the *valfmt* parameter of
+`~.matplotlib.widgets.Slider` and `~.matplotlib.widgets.RangeSlider` now also accepts a
+callable of the form ``valfmt(val: float) -> str``.
+
+WebAgg scroll capture control
+------------------------------
+
+The WebAgg backend now provides the ability to capture scroll events to prevent page
+scrolling when interacting with plots. This can be enabled or disabled via the new
+`.FigureCanvasWebAggCore.set_capture_scroll` and
+`.FigureCanvasWebAggCore.get_capture_scroll` methods.
+
+3D plotting improvements
+========================
+
+Non-linear scales on 3D axes
+----------------------------
+
+Resolving a long-standing issue, 3D axes now support non-linear axis scales such as
+``'log'``, ``'symlog'``, ``'logit'``, ``'asinh'``, and custom ``'function'`` scales,
+just like 2D axes. Use `~.Axes3D.set_xscale`, `~.Axes3D.set_yscale`, and
+`~.Axes3D.set_zscale` to set the scale for each axis independently.
+
+.. plot::
+    :include-source:
+    :alt: A 3D plot with a linear x-axis, logarithmic y-axis, and symlog z-axis.
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+
+    # A sine chirp with increasing frequency and amplitude
+    x = np.linspace(0, 1, 400)  # time
+    y = 10 ** (2 * x)  # frequency, growing exponentially from 1 to 100 Hz
+    phase = 2 * np.pi * (10 ** (2 * x) - 1) / (2 * np.log(10))
+    z = np.sin(phase) * x ** 2 * 10  # amplitude, growing quadratically
+
+    fig = plt.figure()
+    ax = fig.add_subplot(projection='3d')
+    ax.plot(x, y, z)
+
+    ax.set_xlabel('Time (linear)')
+    ax.set_ylabel('Frequency, Hz (log)')
+    ax.set_zlabel('Amplitude (symlog)')
+
+    ax.set_yscale('log')
+    ax.set_zscale('symlog')
+
+    plt.show()
+
+See `matplotlib.scale` for details on all available scales and their parameters.
+
+Snapping 3D rotation angles with Control key
+--------------------------------------------
+
+Rotation of 3D axes now supports snapping to fixed angular increments when holding the
+:kbd:`Control` key during mouse rotation.
+
+The snap step size is controlled by the new :rc:`axes3d.snap_rotation` rcParam. Setting
+it to 0 disables snapping.
+
+For example::
+
+    mpl.rcParams["axes3d.snap_rotation"] = 10
+
+will snap elevation, azimuth, and roll angles to multiples of 10 degrees while rotating
+with the mouse.
+
+3D depth-shading fix
+--------------------
+
+Previously, a slightly buggy method of estimating the visual "depth" of 3D items could
+lead to sudden and unexpected changes in transparency as the plot orientation changed.
+
+Now, the behavior has been made smooth and predictable. A new parameter
+*depthshade_minalpha* has also been added to allow users to set the minimum transparency
+level. Depth-shading is an option for `.Patch3DCollection` and `.Path3DCollection`,
+including 3D scatter plots.
+
+The default values for ``depthshade`` and ``depthshade_minalpha`` are now controlled by
+:rc:`axes3d.depthshade` and :rc:`axes3d.depthshade_minalpha`, respectively.
+
+A simple example:
+
+.. plot::
+    :include-source:
+    :alt: A 3D scatter plot with depth-shading enabled.
+
+    import matplotlib.pyplot as plt
+
+    fig = plt.figure()
+    ax = fig.add_subplot(projection="3d")
+
+    X = [i for i in range(10)]
+    Y = [i for i in range(10)]
+    Z = [i for i in range(10)]
+    S = [(i + 1) * 400 for i in range(10)]
+
+    ax.scatter(
+        xs=X, ys=Y, zs=Z, s=S,
+        depthshade=True,
+        depthshade_minalpha=0.3,
+    )
+    ax.view_init(elev=10, azim=-150, roll=0)
+
+    plt.show()
+
+3D performance improvements
+---------------------------
+
+Draw time for 3D plots has been improved, especially for surface and wireframe plots.
+Users should see up to a 10× speedup in some cases. This should make interacting with 3D
+plots much more responsive.
+
+Other improvements
+==================
+
+Saving figures as GIF works again
+---------------------------------
+
+According to the figure documentation, the ``savefig`` method supports the GIF format
+with the file extension ``.gif``. However, GIF support had been broken since Matplotlib
+2.0.0. It works again.
+
+``CallbackRegistry.disconnect`` allows directly callbacks by function
+-------------------------------------------------------------------------
+
+`.CallbackRegistry` now allows directly passing a function and optionally signal to
+`~.CallbackRegistry.disconnect` instead of needing to track the callback ID returned by
+`~.CallbackRegistry.connect`.
+
+.. code-block:: python
+
+    from matplotlib.cbook import CallbackRegistry
+
+    def my_callback(event):
+        print(event)
+
+    callbacks = CallbackRegistry()
+    callbacks.connect('my_signal', my_callback)
+
+    # Disconnect by function reference instead of callback ID
+    callbacks.disconnect('my_signal', my_callback)
+
+``violin_stats`` simpler *method* parameter
+-------------------------------------------
+
+The *method* parameter of `~.cbook.violin_stats` may now be specified as tuple of
+strings, and has a new default ``("GaussianKDE", "scott")``.  Calling
+`~.cbook.violin_stats` followed by `~.Axes.violin` is therefore now equivalent to
+calling `~.Axes.violinplot`.
+
+.. plot::
+    :include-source:
+    :alt:
+        Example showing violin_stats followed by violin gives the same result as
+        violinplot.
+
+    import matplotlib.pyplot as plt
+    from matplotlib.cbook import violin_stats
+    import numpy as np
+
+    rng = np.random.default_rng(19680801)
+    data = rng.normal(size=(10, 3))
+
+    fig, (ax1, ax2) = plt.subplots(ncols=2, layout='constrained', figsize=(6.4, 3.5))
+
+    # Create the violin plot in one step
+    ax1.violinplot(data)
+    ax1.set_title('One Step')
+
+    # Process the data and then create the violin plot
+    vstats = violin_stats(data)
+    ax2.violin(vstats)
+    ax2.set_title('Two Steps')
+
+    plt.show()
diff --git a/doc/release/release_notes.rst b/doc/release/release_notes.rst
index cbceb4978121..399329c95acf 100644
--- a/doc/release/release_notes.rst
+++ b/doc/release/release_notes.rst
@@ -18,6 +18,7 @@ Version 3.11
 .. toctree::
     :maxdepth: 1
 
+    prev_whats_new/whats_new_3.11.0.rst
     ../api/prev_api_changes/api_changes_3.11.0.rst
     github_stats.rst