python-2.7 - Python PieChart(是否可以做CallOut标签)

Question

有没有用 Python、Matplotlib 等做 CallOut Labels 的例子


Image source

上面有一条线，标签从饼图外部指向……看不到任何可能的例子，它用 Mathplotlib 完成……这可以用 Python 完成吗？？

Answer 1

您可以使用 matplotlib annotations 创建文本标签和注释线。
手动贴标
这是一个示例，其中标签在数据坐标中手动定位，即饼图的中心是 (0,0) 坐标。

import matplotlib.pyplot as plt 

fig, ax= plt.subplots(figsize=(4,4))
plt.subplots_adjust(bottom=0.3)
total = [13,87]
plt.title('How to spot intellectuals on TV')
plt.gca().axis("equal")
pie = plt.pie(total, startangle=93)
labels = ["1. They say sophisticated things", "2. They sit in front of a bookshelf"]

bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
arrowprops=dict(arrowstyle="-",connectionstyle="angle,angleA=0,angleB=90")
kw = dict(xycoords='data',textcoords='data',
          arrowprops=arrowprops, bbox=bbox_props, zorder=0)
plt.gca().annotate("2", xy=(0, 0), xytext=( 1.1, -0.8), **kw )
plt.gca().annotate("1", xy=(0, 0), xytext=(-1.1,  0.8), **kw )

plt.legend(pie[0],labels, loc="center", bbox_to_anchor=(0.5,-0.1))
plt.show()

自动贴标:
我们可以使用楔子的角度在合适的位置自动创建标签。

import matplotlib.pyplot as plt
import numpy as np 

fig, ax= plt.subplots(figsize=(4,4))
plt.subplots_adjust(bottom=0.3)
total = [12,15,12,13,16]
plt.title('My repair strategies')
plt.gca().axis("equal")
patches, texts = pie = plt.pie(total, startangle=5)
labels = ["1. roaring at it", 
          "2. hitting it",
          "3. using superglue",
          "4. using duct tape",
          "5. dismantling it, then ditch it"]

bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
arrowprops=dict(arrowstyle="-",connectionstyle="angle,angleA=0,angleB=90")
kw = dict(xycoords='data',textcoords='data',arrowprops=arrowprops, 
          bbox=bbox_props, zorder=0, va="center")

for i, p in enumerate(patches):
    ang = (p.theta2 - p.theta1)/2.+p.theta1
    y = np.sin(ang/180.*np.pi)
    x = 1.35*np.sign(np.cos(ang/180.*np.pi))
    plt.gca().annotate(str(1+i), xy=(0, 0), xytext=( x, y), **kw )

plt.legend(pie[0],labels, loc="center", bbox_to_anchor=(0.5,-0.2))
plt.show()