通过优化空间在Python中的饼图中添加标签

Question

我有一个数据框，例如：

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Sample data
data = {
    'genus': ['SpeciesA', 'SpeciesB', 'SpeciesC', 'SpeciesD', 'SpeciesE', 'SpeciesF', 'SpeciesG', 'SpeciesH'],
    'count': [10, 2, 1, 1, 1, 1, 1, 1],
    'Type': ['Animal', 'Environment', 'Environment', 'Environment', 'Animal', 'Animal', 'Animal/Environment', 'Animal/Environment']
}

# Create DataFrame
df = pd.DataFrame(data)

>>> df

      genus  count                Type
0  SpeciesA     10              Animal
1  SpeciesB      2         Environment
2  SpeciesC      1         Environment
3  SpeciesD      1         Environment
4  SpeciesE      1              Animal
5  SpeciesF      1              Animal
6  SpeciesG      1  Animal/Environment
7  SpeciesH      1  Animal/Environment

我想使用 python 创建一个饼图，将饼图分为与其总计数成比例的每个类型

到目前为止我可以使用以下方法做到这一点：

# Group by 'Type' and sum up 'count' within each group
type_counts = df.groupby('Type')['count'].sum()

# Create pie chart
plt.figure(figsize=(8, 8))
plt.pie(type_counts, labels=type_counts.index, startangle=140)
plt.title('Distribution of Counts by Type')
plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.
plt.show()

但我现在正在寻找一种在特定子饼图部分中添加属标签的方法。

此类标签应以这种方式包含（A）：

通过优化空间，使标签随机放置在对应的饼图中，不重叠。

或者，如果不可能简单地以这种方式放置它们（B）：

Answer 1

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Sample data
data = {
    'genus': ['SpeciesA', 'SpeciesB', 'SpeciesC', 'SpeciesD', 'SpeciesE', 'SpeciesF', 'SpeciesG', 'SpeciesH'],
    'count': [10, 2, 1, 1, 1, 1, 1, 1],
    'Type': ['Animal', 'Environment', 'Environment', 'Environment', 'Animal', 'Animal', 'Animal/Environment', 'Animal/Environment']
}

# Create DataFrame
df = pd.DataFrame(data)
plt.figure(figsize=(20, 20))
fig, ax = plt.subplots()

size = 0.5
cmap = plt.get_cmap("tab20c")
outer_colors = cmap(np.arange(3)*4)
inner_colors = cmap(np.array([1, 2, 5, 6, 9, 10]))

ax.pie(df.groupby('Type', sort=False)['count'].sum(), radius=1, colors=outer_colors, labels=df['Type'].drop_duplicates(), autopct='%1.1f%%',
       wedgeprops=dict(width=size, edgecolor='w'))

ax.pie(df['count'], radius=1-size, colors=inner_colors, labels=df['genus'], autopct='%1.1f%%',
       wedgeprops=dict(width=size, edgecolor='w'))

ax.set(aspect="equal", title='Distribution 1 and 2')
plt.show()