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Commit2dee159

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Merge branch 'main' into main
2 parents8541748 +dcff41f commit2dee159

28 files changed

+766
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lines changed

‎.github/workflows/do_not_merge.yml‎

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@@ -15,14 +15,16 @@ jobs:
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env:
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has_tag:>-
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${{contains(github.event.pull_request.labels.*.name, 'status: needs comment/discussion') ||
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contains(github.event.pull_request.labels.*.name, 'status: waiting for other PR')}}
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contains(github.event.pull_request.labels.*.name, 'status: waiting for other PR') ||
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contains(github.event.pull_request.labels.*.name, 'DO NOT MERGE') }}
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steps:
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-name:Check for label
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if:${{'true' == env.has_tag}}
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run:|
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echo "This PR cannot be merged because it has one of the following labels: "
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echo "* status: needs comment/discussion"
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echo "* status: waiting for other PR"
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echo "* DO NOT MERGE"
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exit 1
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-name:Allow merging
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if:${{'false' == env.has_tag}}

‎doc/api/axes_api.rst‎

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Axes.eventplot
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Axes.pie
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Axes.pie_label
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Axes.stackplot
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‎doc/api/pyplot_summary.rst‎

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stem
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eventplot
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pie
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pie_label
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stackplot
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broken_barh
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vlines
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``PatchCollection`` legends now supported
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------------------------------------------
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`.PatchCollection` instances now properly display in legends when given a label.
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Previously, labels on `~.PatchCollection` objects were ignored by the legend
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system, requiring users to create manual legend entries.
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..plot::
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:include-source: true
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:alt: The legend entry displays a rectangle matching the visual properties (colors, line styles, line widths) of the first patch in the collection.
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import matplotlib.pyplot as plt
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import matplotlib.patches as mpatches
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from matplotlib.collections import PatchCollection
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fig, ax = plt.subplots()
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patches = [mpatches.Circle((0, 0), 0.1), mpatches.Rectangle((0.5, 0.5), 0.2, 0.3)]
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pc = PatchCollection(patches, facecolor='blue', edgecolor='black', label='My patches')
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ax.add_collection(pc)
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ax.legend() # Now displays the label "My patches"
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plt.show()
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This fix resolves:ghissue:`23998`.
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Adding labels to pie chart wedges
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---------------------------------
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The new `~.Axes.pie_label` method adds a label to each wedge in a pie chart created with
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`~.Axes.pie`. It can take
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* a list of strings, similar to the existing *labels* parameter of `~.Axes.pie`
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* a format string similar to the existing *autopct* parameter of `~.Axes.pie` except
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that it uses the `str.format` method and it can handle absolute values as well as
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fractions/percentages
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For more examples, see:doc:`/gallery/pie_and_polar_charts/pie_label`.
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..plot::
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:include-source: true
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:alt: A pie chart with three labels on each wedge, showing a food type, number, and fraction associated with the wedge.
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import matplotlib.pyplot as plt
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data = [36, 24, 8, 12]
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labels = ['spam', 'eggs', 'bacon', 'sausage']
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fig, ax = plt.subplots()
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pie = ax.pie(data)
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ax.pie_label(pie, labels, distance=1.1)
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ax.pie_label(pie, '{frac:.1%}', distance=0.7)
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ax.pie_label(pie, '{absval:d}', distance=0.4)

‎doc/users/glossary.rst‎

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========
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Glossary
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========
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.. Note for glossary authors:
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The glossary is primarily intended for Matplotlib's own concepts and
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terminology, e.g. figure, artist, backend, etc. We don't want to list
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general terms like "GUI framework", "event loop" or similar.
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The glossary should contain a short definition of the term, aiming at
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a high-level understanding. Use links to redirect to more comprehensive
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explanations and API reference when possible.
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This glossary defines concepts and terminology specific to Matplotlib.
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..glossary::
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Figure
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The outermost container for a Matplotlib graphic. Think of this as the
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canvas to draw on.
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This is implemented in the class `.Figure`. For more details see
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:ref:`figure-intro`.
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Axes
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This is a container for what is often colloquially called a plot/chart/graph.
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It's a data area with:term:`Axis`\es, i.e. coordinate directions,
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and includes data artists like lines, bars etc. as well as
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decorations like title, axis labels, legend.
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Since most "plotting operations" are realized as methods on `~.axes.Axes`
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this is the object users will mostly interact with.
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Note: The term *Axes* was taken over from MATLAB. Think of this as
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a container spanned by the *x*- and *y*-axis, including decoration
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and data.
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Axis
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A direction with a scale. The scale defines the mapping from
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data coordinates to screen coordinates. The Axis also includes
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the ticks and axis label.
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Artist
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The base class for all graphical element that can be drawn.
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Examples are Lines, Rectangles, Text, Ticks, Legend, Axes, ...

‎doc/users/index.rst‎

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getting_started/index
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../install/index
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glossary

‎galleries/examples/misc/svg_filter_pie.py‎

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# We want to draw the shadow for each pie, but we will not use "shadow"
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# option as it doesn't save the references to the shadow patches.
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pies=ax.pie(fracs,explode=explode,labels=labels,autopct='%1.1f%%')
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pie=ax.pie(fracs,explode=explode,labels=labels,autopct='%1.1f%%')
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forwinpies[0]:
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forwinpie.wedges:
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# set the id with the label.
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w.set_gid(w.get_label())
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# we don't want to draw the edge of the pie
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w.set_edgecolor("none")
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forwinpies[0]:
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forwinpie.wedges:
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# create shadow patch
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s=Shadow(w,-0.01,-0.01)
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s.set_gid(w.get_gid()+"_shadow")

‎galleries/examples/pie_and_polar_charts/pie_and_donut_labels.py‎

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Welcome to the Matplotlib bakery. We will create a pie and a donut
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chart through the `pie method <matplotlib.axes.Axes.pie>` and
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show how to label them with a `legend <matplotlib.axes.Axes.legend>`
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as well as with `annotations <matplotlib.axes.Axes.annotate>`.
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as well as with the `pie_label method <matplotlib.axes.Axes.pie>` and
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`annotations <matplotlib.axes.Axes.annotate>`.
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"""
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# %%
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# Now it's time for the pie. Starting with a pie recipe, we create the data
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# and a list of labels from it.
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#
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# We can provide a function to the ``autopct`` argument, which will expand
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# automatic percentage labeling by showing absolute values; we calculate
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# the latter back from relative data and the known sum of all values.
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# We then create the pie and store the returned `~matplotlib.container.PieContainer`
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# object for later.
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#
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# We then create the pie and store the returned objects for later. The first
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# returned element of the returned tuple is a list of the wedges. Those are
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# We can provide the `~matplotlib.container.PieContainer` and a format string to
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# the `~matplotlib.axes.Axes.pie_label` method to automatically label each
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# ingredient's wedge with its weight in grams and percentages.
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#
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# The `~.PieContainer` has a list of patches as one of its attributes. Those are
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# `matplotlib.patches.Wedge` patches, which can directly be used as the handles
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# for a legend. We can use the legend's ``bbox_to_anchor`` argument to position
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# the legend outside of the pie. Here we use the axes coordinates ``(1, 0, 0.5,
@@ -31,32 +34,26 @@
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importmatplotlib.pyplotasplt
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importnumpyasnp
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34-
fig,ax=plt.subplots(figsize=(6,3),subplot_kw=dict(aspect="equal"))
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fig,ax=plt.subplots(figsize=(6,3))
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recipe= ["375 g flour",
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"75 g sugar",
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"250 g butter",
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"300 g berries"]
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41-
data= [float(x.split()[0])forxinrecipe]
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data= [int(x.split()[0])forxinrecipe]
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ingredients= [x.split()[-1]forxinrecipe]
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47+
pie=ax.pie(data)
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45-
deffunc(pct,allvals):
46-
absolute=int(np.round(pct/100.*np.sum(allvals)))
47-
returnf"{pct:.1f}%\n({absolute:d} g)"
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49+
ax.pie_label(pie,'{frac:.1%}\n({absval:d}g)',
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textprops=dict(color="w",size=8,weight="bold"))
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50-
wedges,texts,autotexts=ax.pie(data,autopct=lambdapct:func(pct,data),
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textprops=dict(color="w"))
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ax.legend(wedges,ingredients,
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ax.legend(pie.wedges,ingredients,
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title="Ingredients",
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loc="center left",
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bbox_to_anchor=(1,0,0.5,1))
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58-
plt.setp(autotexts,size=8,weight="bold")
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ax.set_title("Matplotlib bakery: A pie")
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plt.show()
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data= [225,90,50,60,100,5]
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wedges,texts=ax.pie(data,wedgeprops=dict(width=0.5),startangle=-40)
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pie=ax.pie(data,wedgeprops=dict(width=0.5),startangle=-40)
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bbox_props=dict(boxstyle="square,pad=0.3",fc="w",ec="k",lw=0.72)
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kw=dict(arrowprops=dict(arrowstyle="-"),
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bbox=bbox_props,zorder=0,va="center")
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106-
fori,pinenumerate(wedges):
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fori,pinenumerate(pie.wedges):
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ang= (p.theta2-p.theta1)/2.+p.theta1
108105
y=np.sin(np.deg2rad(ang))
109106
x=np.cos(np.deg2rad(ang))
@@ -131,6 +128,7 @@ def func(pct, allvals):
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# in this example:
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#
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# - `matplotlib.axes.Axes.pie` / `matplotlib.pyplot.pie`
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# - `matplotlib.axes.Axes.pie_label` / `matplotlib.pyplot.pie_label`
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# - `matplotlib.axes.Axes.legend` / `matplotlib.pyplot.legend`
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#
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# .. tags::
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"""
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===================
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Labeling pie charts
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===================
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This example illustrates some features of the `~matplotlib.axes.Axes.pie_label`
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method, which adds labels to an existing pie chart created with
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`~matplotlib.axes.Axes.pie`.
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"""
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11+
# %%
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# The simplest option is to provide a list of strings to label each slice of the pie.
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importmatplotlib.pyplotasplt
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data= [36,24,8,12]
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labels= ['spam','eggs','bacon','sausage']
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fig,ax=plt.subplots()
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pie=ax.pie(data)
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ax.pie_label(pie,labels)
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# %%
24+
#
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# If you want the labels outside the pie, set a *distance* greater than 1.
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# This is the distance from the center of the pie as a fraction of its radius.
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fig,ax=plt.subplots()
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pie=ax.pie(data)
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ax.pie_label(pie,labels,distance=1.1)
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# %%
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#
34+
# You can also rotate the labels so they are oriented away from the pie center.
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fig,ax=plt.subplots()
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pie=ax.pie(data)
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ax.pie_label(pie,labels,rotate=True)
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# %%
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#
42+
# Instead of explicit labels, pass a format string to label slices with their values...
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44+
fig,ax=plt.subplots()
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pie=ax.pie(data)
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ax.pie_label(pie,'{absval:.1f}')
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# %%
49+
#
50+
# ...or with their percentages...
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52+
fig,ax=plt.subplots()
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pie=ax.pie(data)
54+
ax.pie_label(pie,'{frac:.1%}')
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# %%
57+
#
58+
# ...or both.
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60+
fig,ax=plt.subplots()
61+
pie=ax.pie(data)
62+
ax.pie_label(pie,'{absval:d}\n{frac:.1%}')
63+
64+
# %%
65+
#
66+
# Font styling can be configured by passing a dictionary to the *textprops* parameter.
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68+
fig,ax=plt.subplots()
69+
pie=ax.pie(data)
70+
ax.pie_label(pie,labels,textprops={'fontsize':'large','color':'white'})
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72+
# %%
73+
#
74+
# `~matplotlib.axes.Axes.pie_label` can be called repeatedly to add multiple sets
75+
# of labels.
76+
77+
# sphinx_gallery_thumbnail_number = -1
78+
79+
fig,ax=plt.subplots()
80+
pie=ax.pie(data)
81+
82+
ax.pie_label(pie,labels,distance=1.1)
83+
ax.pie_label(pie,'{frac:.1%}',distance=0.7)
84+
ax.pie_label(pie,'{absval:d}',distance=0.4)
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86+
plt.show()
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88+
# %%
89+
# .. admonition:: References
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#
91+
# The use of the following functions, methods, classes and modules is shown
92+
# in this example:
93+
#
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# - `matplotlib.axes.Axes.pie` / `matplotlib.pyplot.pie`
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# - `matplotlib.axes.Axes.pie_label` / `matplotlib.pyplot.pie_label`
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#
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# .. tags::
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#
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# plot-type: pie
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# level: beginner

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