matplotlib
diff --git a/‎examples/mplot3d/wire3d_animation_sgskip.py
Lines changed: 1 addition & 1 deletion b/‎examples/mplot3d/wire3d_animation_sgskip.py
Lines changed: 1 addition & 1 deletion
diff --git a/‎examples/pie_and_polar_charts/bar_of_pie.py
Lines changed: 17 additions & 21 deletions b/‎examples/pie_and_polar_charts/bar_of_pie.py
Lines changed: 17 additions & 21 deletions
diff --git a/‎tutorials/intermediate/artists.py
Lines changed: 26 additions & 29 deletions b/‎tutorials/intermediate/artists.py
Lines changed: 26 additions & 29 deletions
@@ -39,7 +39,7 @@ def generate(X, Y, phi):
 for phi in np.linspace(0, 180. / np.pi, 100):
     # If a line collection is already remove it before drawing.
     if wframe:
-        ax.collections.remove(wframe)
+        wframe.remove()
 
     # Plot the new wireframe and pause briefly before continuing.
     Z = generate(X, Y, phi)
 
@@ -19,40 +19,36 @@
 fig.subplots_adjust(wspace=0)
 
 # pie chart parameters
-ratios = [.27, .56, .17]
+overall_ratios = [.27, .56, .17]
 labels = ['Approve', 'Disapprove', 'Undecided']
 explode = [0.1, 0, 0]
 # rotate so that first wedge is split by the x-axis
-angle = -180 * ratios[0]
-ax1.pie(ratios, autopct='%1.1f%%', startangle=angle,
-        labels=labels, explode=explode)
+angle = -180 * overall_ratios[0]
+wedges, *_ = ax1.pie(overall_ratios, autopct='%1.1f%%', startangle=angle,
+                     labels=labels, explode=explode)
 
 # bar chart parameters
-
-xpos = 0
-bottom = 0
-ratios = [.33, .54, .07, .06]
+age_ratios = [.33, .54, .07, .06]
+age_labels = ['Under 35', '35-49', '50-65', 'Over 65']
+bottom = 1
 width = .2
-colors = [[.1, .3, .5], [.1, .3, .3], [.1, .3, .7], [.1, .3, .9]]
 
-for j in range(len(ratios)):
-    height = ratios[j]
-    ax2.bar(xpos, height, width, bottom=bottom, color=colors[j])
-    ypos = bottom + ax2.patches[j].get_height() / 2
-    bottom += height
-    ax2.text(xpos, ypos, "%d%%" % (ax2.patches[j].get_height() * 100),
-             ha='center')
+# Adding from the top matches the legend.
+for j, (height, label) in enumerate(reversed([*zip(age_ratios, age_labels)])):
+    bottom -= height
+    bc = ax2.bar(0, height, width, bottom=bottom, color='C0', label=label,
+                 alpha=0.1 + 0.25 * j)
+    ax2.bar_label(bc, labels=[f"{height:.0%}"], label_type='center')
 
 ax2.set_title('Age of approvers')
-ax2.legend(('50-65', 'Over 65', '35-49', 'Under 35'))
+ax2.legend()
 ax2.axis('off')
 ax2.set_xlim(- 2.5 * width, 2.5 * width)
 
 # use ConnectionPatch to draw lines between the two plots
-# get the wedge data
-theta1, theta2 = ax1.patches[0].theta1, ax1.patches[0].theta2
-center, r = ax1.patches[0].center, ax1.patches[0].r
-bar_height = sum([item.get_height() for item in ax2.patches])
+theta1, theta2 = wedges[0].theta1, wedges[0].theta2
+center, r = wedges[0].center, wedges[0].r
+bar_height = sum(age_ratios)
 
 # draw top connecting line
 x = r * np.cos(np.pi / 180 * theta2) + center[0]
 
@@ -79,13 +79,11 @@ class in the Matplotlib API, and the one you will be working with most
     line, = ax.plot(t, s, color='blue', lw=2)
 
 In this example, ``ax`` is the ``Axes`` instance created by the
-``fig.add_subplot`` call above (remember ``Subplot`` is just a
-subclass of ``Axes``) and when you call ``ax.plot``, it creates a
-``Line2D`` instance and adds it to the :attr:`Axes.lines
-<matplotlib.axes.Axes.lines>` list.  In the interactive `IPython
-<https://ipython.org/>`_ session below, you can see that the
-``Axes.lines`` list is length one and contains the same line that was
-returned by the ``line, = ax.plot...`` call:
+``fig.add_subplot`` call above (remember ``Subplot`` is just a subclass of
+``Axes``) and when you call ``ax.plot``, it creates a ``Line2D`` instance and
+adds it to the ``Axes``.  In the interactive `IPython <https://ipython.org/>`_
+session below, you can see that the ``Axes.lines`` list is length one and
+contains the same line that was returned by the ``line, = ax.plot...`` call:
 
 .. sourcecode:: ipython
 
@@ -97,11 +95,10 @@ class in the Matplotlib API, and the one you will be working with most
 
 If you make subsequent calls to ``ax.plot`` (and the hold state is "on"
 which is the default) then additional lines will be added to the list.
-You can remove lines later simply by calling the list methods; either
-of these will work::
+You can remove a line later by calling its ``remove`` method::
 
-    del ax.lines[0]
-    ax.lines.remove(line)  # one or the other, not both!
+    line = ax.lines[0]
+    line.remove()
 
 The Axes also has helper methods to configure and decorate the x-axis
 and y-axis tick, tick labels and axis labels::
@@ -386,11 +383,10 @@ class in the Matplotlib API, and the one you will be working with most
 #     rect.set_facecolor('green')
 #
 # When you call a plotting method, e.g., the canonical
-# :meth:`~matplotlib.axes.Axes.plot` and pass in arrays or lists of
-# values, the method will create a :meth:`matplotlib.lines.Line2D`
-# instance, update the line with all the ``Line2D`` properties passed as
-# keyword arguments, add the line to the :attr:`Axes.lines
-# <matplotlib.axes.Axes.lines>` container, and returns it to you:
+# `~matplotlib.axes.Axes.plot` and pass in arrays or lists of values, the
+# method will create a `matplotlib.lines.Line2D` instance, update the line with
+# all the ``Line2D`` properties passed as keyword arguments, add the line to
+# the ``Axes``, and return it to you:
 #
 # .. sourcecode:: ipython
 #
@@ -423,19 +419,20 @@ class in the Matplotlib API, and the one you will be working with most
 #     In [235]: print(len(ax.patches))
 #     Out[235]: 50
 #
-# You should not add objects directly to the ``Axes.lines`` or
-# ``Axes.patches`` lists unless you know exactly what you are doing,
-# because the ``Axes`` needs to do a few things when it creates and adds
-# an object.  It sets the figure and axes property of the ``Artist``, as
-# well as the default ``Axes`` transformation (unless a transformation
-# is set).  It also inspects the data contained in the ``Artist`` to
-# update the data structures controlling auto-scaling, so that the view
-# limits can be adjusted to contain the plotted data.  You can,
-# nonetheless, create objects yourself and add them directly to the
-# ``Axes`` using helper methods like
-# :meth:`~matplotlib.axes.Axes.add_line` and
-# :meth:`~matplotlib.axes.Axes.add_patch`.  Here is an annotated
-# interactive session illustrating what is going on:
+# You should not add objects directly to the ``Axes.lines`` or ``Axes.patches``
+# lists, because the ``Axes`` needs to do a few things when it creates and adds
+# an object:
+#
+# - It sets the ``figure`` and ``axes`` property of the ``Artist``;
+# - It sets the default ``Axes`` transformation (unless one is already set);
+# - It inspects the data contained in the ``Artist`` to update the data
+#   structures controlling auto-scaling, so that the view limits can be
+#   adjusted to contain the plotted data.
+#
+# You can, nonetheless, create objects yourself and add them directly to the
+# ``Axes`` using helper methods like `~matplotlib.axes.Axes.add_line` and
+# `~matplotlib.axes.Axes.add_patch`.  Here is an annotated interactive session
+# illustrating what is going on:
 #
 # .. sourcecode:: ipython
 #