Dec 22, 2024
diff --git a/doc/api/next_api_changes/behavior/29152_REC.rst b/doc/api/next_api_changes/behavior/29152_REC.rst
 Return value of ``pie``
 ~~~~~~~~~~~~~~~~~~~~~~~
 Previously, if no *labels* were passed to `~.Axes.pie`, and *labeldistance* was
 not ``None``, empty text labels would be added to the axes and returned.  This
 is no longer the case.  To continue creating empty labels, either pass an empty
 string with the new *wedge_labels* parameter ``wedge_labels=''`` or, for
 compatibility with older Matplotlib versions, pass an empty string for each wedge
 via the *labels* parameter, i.e. ``labels=[''] * number_of_wedges``.  Note the
 latter option will stop working at Matplotlib 3.16.
diff --git a/doc/api/next_api_changes/deprecations/29152_REC.rst b/doc/api/next_api_changes/deprecations/29152_REC.rst
 ``pie`` *labels* and *labeldistance* parameters
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 Currently the *labels* parameter of `~.Axes.pie` is used both for annotating the
 pie wedges directly, and for automatic legend entries.  For consistency
 with other plotting methods, in future *labels* will only be used for the legend.

 The *labeldistance* parameter will therefore default to ``None`` from Matplotlib
 3.14, when it will also be deprecated and then removed in Matplotlib 3.16.  To
 preserve the existing behavior for now, set ``labeldistance=1.1``.  For the longer
 term, use the new *wedge_labels* parameter of `~.Axes.pie` instead of *labels*.
diff --git a/doc/release/next_whats_new/pie_wedge_labels.rst b/doc/release/next_whats_new/pie_wedge_labels.rst
 New *wedge_labels* parameter for pie
 ------------------------------------

 `~.Axes.pie` now accepts a *wedge_labels* parameter which may be used to
 annotate the wedges of the pie chart.  It can take

 * a list of strings, similar to the existing *labels* parameter
 * a format string in analogy to the existing *autopct* parameter except that it
  uses the `str.format` method, and it can handle absolute values as well as
  fractions/percentages

 To add multiple labels per wedge, *wedge_labels* can take a sequence of any combination
 of the above two options.

 *wedge_labels* have accompanying *wedge_label_distance* and *rotate_wedge_labels*
 parameters, to customise the position and rotation of the labels.

 For examples, see :doc:`/gallery/pie_and_polar_charts/pie_features`.
diff --git a/galleries/examples/misc/svg_filter_pie.py b/galleries/examples/misc/svg_filter_pie.py

 # We want to draw the shadow for each pie, but we will not use "shadow"
 # option as it doesn't save the references to the shadow patches.
 pies = ax.pie(fracs, explode=explode, labels=labels, autopct='%1.1f%%')
 pies = ax.pie(fracs, explode=explode, wedge_labels=[labels, '{frac:.1%}'],
              wedge_label_distance=[1.1, 0.6])

 for win pies[0]:
 for w, labelinzip(pies[0], labels):
    # set the id with the label.
    w.set_gid(w.get_label())
    w.set_gid(label)

    # we don't want to draw the edge of the pie
    w.set_edgecolor("none")
diff --git a/galleries/examples/pie_and_polar_charts/bar_of_pie.py b/galleries/examples/pie_and_polar_charts/bar_of_pie.py
 explode = [0.1, 0, 0]
 # rotate so that first wedge is split by the x-axis
 angle = -180 * overall_ratios[0]
 wedges, *_ = ax1.pie(overall_ratios, autopct='%1.1f%%', startangle=angle,
                     labels=labels, explode=explode)
 wedges, *_ = ax1.pie(
    overall_ratios, startangle=angle, explode=explode,
    wedge_labels=[labels, '{frac:.1%}'], wedge_label_distance=[1.1, 0.6])

 # bar chart parameters
 age_ratios = [.33, .54, .07, .06]
diff --git a/galleries/examples/pie_and_polar_charts/pie_and_donut_labels.py b/galleries/examples/pie_and_polar_charts/pie_and_donut_labels.py
 # Now it's time for the pie. Starting with a pie recipe, we create the data
 # and a list of labels from it.
 #
 # We can provide afunctionto the``autopct`` argument, which will expand
 #automatic percentage labeling by showing absolute values; we calculate
 #the latter back from relative data and the known sum of all values.
 # We can provide aformat stringto the*wedge_labels* parameter, to
 #automatically label each ingredient's wedge with its weight in grams and
 #percentages.
 #
 # We then create the pie and store the returned objects for later.  The first
 # returned element of the returned tuple is a list of the wedges.  Those are
 import matplotlib.pyplot as plt
 import numpy as np

 fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
 fig, ax = plt.subplots(figsize=(6, 3))

 recipe = ["375 g flour",
          "75 g sugar",
          "250 g butter",
          "300 g berries"]

 data = [float(x.split()[0]) for x in recipe]
 data = [int(x.split()[0]) for x in recipe]
 ingredients = [x.split()[-1] for x in recipe]


 def func(pct, allvals):
    absolute = int(np.round(pct/100.*np.sum(allvals)))
    return f"{pct:.1f}%\n({absolute:d} g)"


 wedges, texts, autotexts = ax.pie(data, autopct=lambda pct: func(pct, data),
                                  textprops=dict(color="w"))
 wedges, texts = ax.pie(data, wedge_labels='{frac:.1%}\n({absval:d}g)',
                       textprops=dict(color="w", size=8, weight="bold"))

 ax.legend(wedges, ingredients,
          title="Ingredients",
          loc="center left",
          bbox_to_anchor=(1, 0, 0.5, 1))

 plt.setp(autotexts, size=8, weight="bold")

 ax.set_title("Matplotlib bakery: A pie")

 plt.show()

 data = [225, 90, 50, 60, 100, 5]

 wedges,texts = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)
 wedges,_ = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)

 bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
 kw = dict(arrowprops=dict(arrowstyle="-"),
diff --git a/galleries/examples/pie_and_polar_charts/pie_features.py b/galleries/examples/pie_and_polar_charts/pie_features.py
 # ------------
 #
 # Plot a pie chart of animals and label the slices. To add
 # labels, pass a list of labels to the *labels* parameter
 # labels, pass a list of labels to the *wedge_labels* parameter.

 import matplotlib.pyplot as plt

 labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
 sizes = [15, 30, 45, 10]
 sizes = [12, 24, 36, 8]

 fig, ax = plt.subplots()
 ax.pie(sizes,labels=labels)
 ax.pie(sizes,wedge_labels=labels)

 # %%
 # Each slice of the pie chart is a `.patches.Wedge` object; therefore in
 # addition to the customizations shown here, each wedge can be customized using
 # the *wedgeprops* argument, as demonstrated in
 # :doc:`/gallery/pie_and_polar_charts/nested_pie`.
 #
 # Controlling label positions
 # ---------------------------
 # If you want the labels outside the pie, set a *wedge_label_distance* greater than 1.
 # This is the distance from the center of the pie as a fraction of its radius.

 fig, ax = plt.subplots()
 ax.pie(sizes, wedge_labels=labels, wedge_label_distance=1.1)

 # %%
 #
 # Auto-label slices
 # -----------------
 #
 # Pass a function or format string to *autopct* to label slices.
 # Pass a format string to *wedge_labels* to label slices with their values...

 fig, ax = plt.subplots()
 ax.pie(sizes, wedge_labels='{absval:.1f}')

 # %%
 #
 # ...or with their percentages...

 fig, ax = plt.subplots()
 ax.pie(sizes, wedge_labels='{frac:.1%}')

 # %%
 #
 # ...or both.

 fig, ax = plt.subplots()
 ax.pie(sizes, labels=labels, autopct='%1.1f%%')
 ax.pie(sizes, wedge_labels='{absval:d}\n{frac:.1%}')


 # %%
 #
 # Multiple labels
 # ---------------
 #
 # Pass both a list of labels and a format string to *wedge_labels*, with a
 # corresponding *wedge_label_distance* for each.

 fig, ax = plt.subplots()
 ax.pie(sizes, wedge_labels=[labels, '{frac:.1%}'], wedge_label_distance=[1.1, 0.6])

 # %%
 # By default, the label values are obtained from the percent size of the slice.
 #
 # Color slices
 # ------------
 #
 # Pass a list of colors to *colors* to set the color of each slice.

 fig, ax = plt.subplots()
 ax.pie(sizes,labels=labels,
 ax.pie(sizes,wedge_labels=labels, wedge_label_distance=1.1,
       colors=['olivedrab', 'rosybrown', 'gray', 'saddlebrown'])

 # %%
 # Pass a list of hatch patterns to *hatch* to set the pattern of each slice.

 fig, ax = plt.subplots()
 ax.pie(sizes, labels=labels, hatch=['**O', 'oO', 'O.O', '.||.'])

 # %%
 # Swap label and autopct text positions
 # -------------------------------------
 # Use the *labeldistance* and *pctdistance* parameters to position the *labels*
 # and *autopct* text respectively.

 fig, ax = plt.subplots()
 ax.pie(sizes, labels=labels, autopct='%1.1f%%',
       pctdistance=1.25, labeldistance=.6)
 ax.pie(sizes, wedge_labels=labels, wedge_label_distance=1.1,
       hatch=['**O', 'oO', 'O.O', '.||.'])

 # %%
 # *labeldistance* and *pctdistance* are ratios of the radius; therefore they
 # vary between ``0`` for the center of the pie and ``1`` for the edge of the
 # pie, and can be set to greater than ``1`` to place text outside the pie.
 #
 # Explode, shade, and rotate slices
 # ---------------------------------
 explode = (0, 0.1, 0, 0)  # only "explode" the 2nd slice (i.e. 'Hogs')

 fig, ax = plt.subplots()
 ax.pie(sizes, explode=explode,labels=labels,autopct='%1.1f%%',
       shadow=True, startangle=90)
 ax.pie(sizes, explode=explode,wedge_labels=[labels,'{frac:.1%}'],
 wedge_label_distance=[1.1, 0.6],shadow=True, startangle=90)
 plt.show()

 # %%

 fig, ax = plt.subplots()

 ax.pie(sizes, labels=labels, autopct='%.0f%%',
 ax.pie(sizes, wedge_labels=[labels, '{frac:.1%}'],
       wedge_label_distance=[1.1, 0.6],
       textprops={'size': 'small'}, radius=0.5)
 plt.show()

 # the `.Shadow` patch. This can be used to modify the default shadow.

 fig, ax = plt.subplots()
 ax.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',
 ax.pie(sizes, explode=explode, wedge_labels=[labels, '{frac:.1%}'],
       wedge_label_distance=[1.1, 0.6],
       shadow={'ox': -0.04, 'edgecolor': 'none', 'shade': 0.9}, startangle=90)
 plt.show()

diff --git a/lib/matplotlib/__init__.py b/lib/matplotlib/__init__.py
    return docstring.replace('    DATA_PARAMETER_PLACEHOLDER', data_doc)


 def _preprocess_data(func=None, *, replace_names=None, label_namer=None):
 def _preprocess_data(func=None, *, replace_names=None, replace_names_multi=None,
                     label_namer=None):
    """
    A decorator to add a 'data' kwarg to a function.

    replace_names : list of str or None, default: None
        The list of parameter names for which lookup into *data* should be
        attempted. If None, replacement is attempted for all arguments.
    replace_names_multi : list of str or None, default: None
        As for *replace_names*, but if a sequence is passed, a lookup into *data*
        will be attempted for each element of the sequence.  Currently only
        supported for parameters named in the function signature (not those passed via
        *args or **kwargs).
    label_namer : str, default: None
        If set e.g. to "namer" (which must be a kwarg in the function's
        signature -- not as ``**kwargs``), if the *namer* argument passed in is
    if func is None:  # Return the actual decorator.
        return functools.partial(
            _preprocess_data,
            replace_names=replace_names, label_namer=label_namer)
            replace_names=replace_names, replace_names_multi=replace_names_multi,
            label_namer=label_namer)

    sig = inspect.signature(func)
    varargs_name = None
            else:
                if replace_names is None or k in replace_names:
                    bound.arguments[k] = _replacer(data, v)
                if (replace_names_multi is not None and k in replace_names_multi and
                        not cbook.is_scalar_or_string(v)):
                    bound.arguments[k] = [_replacer(data, vi) for vi in v]

        new_args = bound.args
        new_kwargs = bound.kwargs
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,9 @@
		Return value of ``pie``
		~~~~~~~~~~~~~~~~~~~~~~~
		Previously, if no labels were passed to `~.Axes.pie`, and labeldistance was
		not ``None``, empty text labels would be added to the axes and returned. This
		is no longer the case. To continue creating empty labels, either pass an empty
		string with the new wedge_labels parameter ``wedge_labels=''`` or, for
		compatibility with older Matplotlib versions, pass an empty string for each wedge
		via the labels parameter, i.e. ``labels=[''] * number_of_wedges``. Note the
		latter option will stop working at Matplotlib 3.16.
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,10 @@
		``pie`` labels and labeldistance parameters
		~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
		Currently the labels parameter of `~.Axes.pie` is used both for annotating the
		pie wedges directly, and for automatic legend entries. For consistency
		with other plotting methods, in future labels will only be used for the legend.

		The labeldistance parameter will therefore default to ``None`` from Matplotlib
		3.14, when it will also be deprecated and then removed in Matplotlib 3.16. To
		preserve the existing behavior for now, set ``labeldistance=1.1``. For the longer
		term, use the new wedge_labels parameter of `~.Axes.pie` instead of labels.
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,18 @@
		New wedge_labels parameter for pie
		------------------------------------

		`~.Axes.pie` now accepts a wedge_labels parameter which may be used to
		annotate the wedges of the pie chart. It can take

		* a list of strings, similar to the existing labels parameter
		* a format string in analogy to the existing autopct parameter except that it
		uses the `str.format` method, and it can handle absolute values as well as
		fractions/percentages

		To add multiple labels per wedge, wedge_labels can take a sequence of any combination
		of the above two options.

		wedge_labels have accompanying wedge_label_distance and rotate_wedge_labels
		parameters, to customise the position and rotation of the labels.

		For examples, see :doc:`/gallery/pie_and_polar_charts/pie_features`.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -28,11 +28,12 @@

		# We want to draw the shadow for each pie, but we will not use "shadow"
		# option as it doesn't save the references to the shadow patches.
		pies = ax.pie(fracs, explode=explode, labels=labels, autopct='%1.1f%%')
		pies = ax.pie(fracs, explode=explode, wedge_labels=[labels, '{frac:.1%}'],
		wedge_label_distance=[1.1, 0.6])

		for win pies[0]:
		for w, labelinzip(pies[0], labels):
		# set the id with the label.
		w.set_gid(w.get_label())
		w.set_gid(label)

		# we don't want to draw the edge of the pie
		w.set_edgecolor("none")
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -25,8 +25,9 @@
		explode = [0.1, 0, 0]
		# rotate so that first wedge is split by the x-axis
		angle = -180 * overall_ratios[0]
		wedges, *_ = ax1.pie(overall_ratios, autopct='%1.1f%%', startangle=angle,
		labels=labels, explode=explode)
		wedges, *_ = ax1.pie(
		overall_ratios, startangle=angle, explode=explode,
		wedge_labels=[labels, '{frac:.1%}'], wedge_label_distance=[1.1, 0.6])

		# bar chart parameters
		age_ratios = [.33, .54, .07, .06]
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -15,9 +15,9 @@
		# Now it's time for the pie. Starting with a pie recipe, we create the data
		# and a list of labels from it.
		#
		# We can provide afunctionto the``autopct`` argument, which will expand
		#automatic percentage labeling by showing absolute values; we calculate
		#the latter back from relative data and the known sum of all values.
		# We can provide aformat stringto thewedge_labels parameter, to
		#automatically label each ingredient's wedge with its weight in grams and
		#percentages.
		#
		# We then create the pie and store the returned objects for later. The first
		# returned element of the returned tuple is a list of the wedges. Those are
Expand All		@@ -31,32 +31,24 @@
		import matplotlib.pyplot as plt
		import numpy as np

		fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
		fig, ax = plt.subplots(figsize=(6, 3))

		recipe = ["375 g flour",
		"75 g sugar",
		"250 g butter",
		"300 g berries"]

		data = [float(x.split()[0]) for x in recipe]
		data = [int(x.split()[0]) for x in recipe]
		ingredients = [x.split()[-1] for x in recipe]


		def func(pct, allvals):
		absolute = int(np.round(pct/100.*np.sum(allvals)))
		return f"{pct:.1f}%\n({absolute:d} g)"


		wedges, texts, autotexts = ax.pie(data, autopct=lambda pct: func(pct, data),
		textprops=dict(color="w"))
		wedges, texts = ax.pie(data, wedge_labels='{frac:.1%}\n({absval:d}g)',
		textprops=dict(color="w", size=8, weight="bold"))

		ax.legend(wedges, ingredients,
		title="Ingredients",
		loc="center left",
		bbox_to_anchor=(1, 0, 0.5, 1))

		plt.setp(autotexts, size=8, weight="bold")

		ax.set_title("Matplotlib bakery: A pie")

		plt.show()
Expand DownExpand Up		@@ -97,7 +89,7 @@ def func(pct, allvals):

		data = [225, 90, 50, 60, 100, 5]

		wedges,texts = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)
		wedges,_ = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)

		bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
		kw = dict(arrowprops=dict(arrowstyle="-"),
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -15,40 +15,75 @@
		# ------------
		#
		# Plot a pie chart of animals and label the slices. To add
		# labels, pass a list of labels to the labels parameter
		# labels, pass a list of labels to the wedge_labels parameter.

		import matplotlib.pyplot as plt

		labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
		sizes = [15, 30, 45, 10]
		sizes = [12, 24, 36, 8]

		fig, ax = plt.subplots()
		ax.pie(sizes,labels=labels)
		ax.pie(sizes,wedge_labels=labels)

		# %%
		# Each slice of the pie chart is a `.patches.Wedge` object; therefore in
		# addition to the customizations shown here, each wedge can be customized using
		# the wedgeprops argument, as demonstrated in
		# :doc:`/gallery/pie_and_polar_charts/nested_pie`.
		#
		# Controlling label positions
		# ---------------------------
		# If you want the labels outside the pie, set a wedge_label_distance greater than 1.
		# This is the distance from the center of the pie as a fraction of its radius.

		fig, ax = plt.subplots()
		ax.pie(sizes, wedge_labels=labels, wedge_label_distance=1.1)

		# %%
		#
		# Auto-label slices
		# -----------------
		#
		# Pass a function or format string to autopct to label slices.
		# Pass a format string to wedge_labels to label slices with their values...

		fig, ax = plt.subplots()
		ax.pie(sizes, wedge_labels='{absval:.1f}')

		# %%
		#
		# ...or with their percentages...

		fig, ax = plt.subplots()
		ax.pie(sizes, wedge_labels='{frac:.1%}')

		# %%
		#
		# ...or both.

		fig, ax = plt.subplots()
		ax.pie(sizes, labels=labels, autopct='%1.1f%%')
		ax.pie(sizes, wedge_labels='{absval:d}\n{frac:.1%}')


		# %%
		#
		# Multiple labels
		# ---------------
		#
		# Pass both a list of labels and a format string to wedge_labels, with a
		# corresponding wedge_label_distance for each.

		fig, ax = plt.subplots()
		ax.pie(sizes, wedge_labels=[labels, '{frac:.1%}'], wedge_label_distance=[1.1, 0.6])

		# %%
		# By default, the label values are obtained from the percent size of the slice.
		#
		# Color slices
		# ------------
		#
		# Pass a list of colors to colors to set the color of each slice.

		fig, ax = plt.subplots()
		ax.pie(sizes,labels=labels,
		ax.pie(sizes,wedge_labels=labels, wedge_label_distance=1.1,
		colors=['olivedrab', 'rosybrown', 'gray', 'saddlebrown'])

		# %%
Expand All		@@ -58,22 +93,10 @@
		# Pass a list of hatch patterns to hatch to set the pattern of each slice.

		fig, ax = plt.subplots()
		ax.pie(sizes, labels=labels, hatch=['**O', 'oO', 'O.O', '.\|\|.'])

		# %%
		# Swap label and autopct text positions
		# -------------------------------------
		# Use the labeldistance and pctdistance parameters to position the labels
		# and autopct text respectively.

		fig, ax = plt.subplots()
		ax.pie(sizes, labels=labels, autopct='%1.1f%%',
		pctdistance=1.25, labeldistance=.6)
		ax.pie(sizes, wedge_labels=labels, wedge_label_distance=1.1,
		hatch=['**O', 'oO', 'O.O', '.\|\|.'])

		# %%
		# labeldistance and pctdistance are ratios of the radius; therefore they
		# vary between ``0`` for the center of the pie and ``1`` for the edge of the
		# pie, and can be set to greater than ``1`` to place text outside the pie.
		#
		# Explode, shade, and rotate slices
		# ---------------------------------
Expand All		@@ -89,8 +112,8 @@
		explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')

		fig, ax = plt.subplots()
		ax.pie(sizes, explode=explode,labels=labels,autopct='%1.1f%%',
		shadow=True, startangle=90)
		ax.pie(sizes, explode=explode,wedge_labels=[labels,'{frac:.1%}'],
		wedge_label_distance=[1.1, 0.6],shadow=True, startangle=90)
		plt.show()

		# %%
Expand All		@@ -107,7 +130,8 @@

		fig, ax = plt.subplots()

		ax.pie(sizes, labels=labels, autopct='%.0f%%',
		ax.pie(sizes, wedge_labels=[labels, '{frac:.1%}'],
		wedge_label_distance=[1.1, 0.6],
		textprops={'size': 'small'}, radius=0.5)
		plt.show()

Expand All		@@ -119,7 +143,8 @@
		# the `.Shadow` patch. This can be used to modify the default shadow.

		fig, ax = plt.subplots()
		ax.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',
		ax.pie(sizes, explode=explode, wedge_labels=[labels, '{frac:.1%}'],
		wedge_label_distance=[1.1, 0.6],
		shadow={'ox': -0.04, 'edgecolor': 'none', 'shade': 0.9}, startangle=90)
		plt.show()

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -1429,7 +1429,8 @@ def _add_data_doc(docstring, replace_names):
		return docstring.replace(' DATA_PARAMETER_PLACEHOLDER', data_doc)


		def _preprocess_data(func=None, *, replace_names=None, label_namer=None):
		def _preprocess_data(func=None, *, replace_names=None, replace_names_multi=None,
		label_namer=None):
		"""
		A decorator to add a 'data' kwarg to a function.

Expand All		@@ -1454,6 +1455,11 @@ def func(ax, args, *kwargs): ...
		replace_names : list of str or None, default: None
		The list of parameter names for which lookup into data should be
		attempted. If None, replacement is attempted for all arguments.
		replace_names_multi : list of str or None, default: None
		As for replace_names, but if a sequence is passed, a lookup into data
		will be attempted for each element of the sequence. Currently only
		supported for parameters named in the function signature (not those passed via
		args or *kwargs).
		label_namer : str, default: None
		If set e.g. to "namer" (which must be a kwarg in the function's
		signature -- not as ``*kwargs``), if the namer* argument passed in is
Expand All		@@ -1471,7 +1477,8 @@ def func(foo, label=None): ...
		if func is None: # Return the actual decorator.
		return functools.partial(
		_preprocess_data,
		replace_names=replace_names, label_namer=label_namer)
		replace_names=replace_names, replace_names_multi=replace_names_multi,
		label_namer=label_namer)

		sig = inspect.signature(func)
		varargs_name = None
Expand DownExpand Up		@@ -1523,6 +1530,9 @@ def inner(ax, args, data=None, *kwargs):
		else:
		if replace_names is None or k in replace_names:
		bound.arguments[k] = _replacer(data, v)
		if (replace_names_multi is not None and k in replace_names_multi and
		not cbook.is_scalar_or_string(v)):
		bound.arguments[k] = [_replacer(data, vi) for vi in v]

		new_args = bound.args
		new_kwargs = bound.kwargs
Expand Down