具有共享图例的多个饼图

我认为，在这种情况下，手动绘制事物matplotlib比使用pandas数据框绘制方法容易。这样，您就可以控制更多。绘制所有饼图后，可以仅在第一个轴上添加图例：

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'], 
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(1,4, figsize=(10,5))
for ax, col in zip(axes, df.columns):
    ax.pie(df[col], labels=df.index, autopct='%.2f', colors=colors)
    ax.set(ylabel='', title=col, aspect='equal')

axes[0].legend(bbox_to_anchor=(0, 0.5))

fig.savefig('your_file.png') # Or whichever format you'd like
plt.show()

改用pandas绘图方法

但是，如果您希望使用绘图方法：

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'],
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(1,4, figsize=(10,5))
for ax, col in zip(axes, df.columns):
    df[col].plot(kind='pie', legend=False, ax=ax, autopct='%0.2f', title=col,
                 colors=colors)
    ax.set(ylabel='', aspect='equal')

axes[0].legend(bbox_to_anchor=(0, 0.5))

fig.savefig('your_file.png')
plt.show()

两者产生相同的结果。

重新布置子图网格

If you'd like to have a 2x2 or other grid arrangement of plots, plt.subplots will return a 2D array of axes. Therefore, you'd need to iterate over axes.flat instead of axes directly.

For example:

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'], 
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(nrows=2, ncols=2)
for ax, col in zip(axes.flat, df.columns):
    ax.pie(df[col], labels=df.index, autopct='%.2f', colors=colors)
    ax.set(ylabel='', title=col, aspect='equal')

axes[0, 0].legend(bbox_to_anchor=(0, 0.5))

fig.savefig('your_file.png') # Or whichever format you'd like
plt.show()

Other Grid Arrangements

If you'd like a grid arrangement that has more axes than the amount of data you have, you'll need to hide any axes that you don't plot on. For example:

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'], 
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(nrows=2, ncols=3)
for ax in axes.flat:
    ax.axis('off')

for ax, col in zip(axes.flat, df.columns):
    ax.pie(df[col], labels=df.index, autopct='%.2f', colors=colors)
    ax.set(ylabel='', title=col, aspect='equal')

axes[0, 0].legend(bbox_to_anchor=(0, 0.5))

fig.savefig('your_file.png') # Or whichever format you'd like
plt.show()

Omitting Labels

If you don't want the labels around the outside, omit the labels argument to pie. However, when we do this, we'll need to build up the legend manually by passing in artists and labels for the artists. This is also a good time to demonstrate using fig.legend to align the single legend relative to the figure. We'll place the legend in the center, in this case:

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'],
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(nrows=2, ncols=2)
for ax, col in zip(axes.flat, df.columns):
    artists = ax.pie(df[col], autopct='%.2f', colors=colors)
    ax.set(ylabel='', title=col, aspect='equal')

fig.legend(artists[0], df.index, loc='center')

plt.show()

Moving Percentage Labels Outside

类似地，百分比标签的径向位置由pctdistancekwarg控制。大于1的值会将百分比标签移到饼图之外。但是，百分比标签（居中）的默认文本对齐方式假定它们位于饼图内部。一旦将它们移出饼图，我们将需要使用其他对齐约定。

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456)
import pandas as pd

def align_labels(labels):
    for text in labels:
        x, y = text.get_position()
        h_align = 'left' if x > 0 else 'right'
        v_align = 'bottom' if y > 0 else 'top'
        text.set(ha=h_align, va=v_align)

df = pd.DataFrame(3 * np.random.rand(4, 4), index=['a', 'b', 'c', 'd'],
                  columns=['x', 'y','z','w'])

plt.style.use('ggplot')
colors = plt.rcParams['axes.color_cycle']

fig, axes = plt.subplots(nrows=2, ncols=2)
for ax, col in zip(axes.flat, df.columns):
    artists = ax.pie(df[col], autopct='%.2f', pctdistance=1.05, colors=colors)
    ax.set(ylabel='', title=col, aspect='equal')
    align_labels(artists[-1])

fig.legend(artists[0], df.index, loc='center')

plt.show()