局部整体（七）利用python绘制圆形嵌套图

圆形嵌套图（ Circular Packing）简介

将一组组圆形互相嵌套起来，以显示数据的层次关系，类似于矩形树图。数据集中每个实体都由一个圆表示，圆圈大小与其代表的值成正比，相对于treemap，圆堆图更直观简洁，虽然利用率上有缺陷。

快速绘制

基于circlify

import circlify
import matplotlib.pyplot as plt# 自定义数据
data = [{'id': 'World', 'datum': 6964195249, 'children' : [{'id' : "North America", 'datum': 450448697,'children' : [{'id' : "United States", 'datum' : 308865000},{'id' : "Mexico", 'datum' : 107550697},{'id' : "Canada", 'datum' : 34033000} ]},{'id' : "South America", 'datum' : 278095425, 'children' : [{'id' : "Brazil", 'datum' : 192612000},{'id' : "Colombia", 'datum' : 45349000},{'id' : "Argentina", 'datum' : 40134425}]},{'id' : "Europe", 'datum' : 209246682,  'children' : [{'id' : "Germany", 'datum' : 81757600},{'id' : "France", 'datum' : 65447374},{'id' : "United Kingdom", 'datum' : 62041708}]},{'id' : "Africa", 'datum' : 311929000,  'children' : [{'id' : "Nigeria", 'datum' : 154729000},{'id' : "Ethiopia", 'datum' : 79221000},{'id' : "Egypt", 'datum' : 77979000}]},{'id' : "Asia", 'datum' : 2745929500,  'children' : [{'id' : "China", 'datum' : 1336335000},{'id' : "India", 'datum' : 1178225000},{'id' : "Indonesia", 'datum' : 231369500}]}]}]# 计算圆的位置
circles = circlify.circlify(data, show_enclosure=False, # 不展示最外层的圈target_enclosure=circlify.Circle(x=0, y=0, r=1)
)# 初始化布局
fig, ax = plt.subplots(figsize=(8,8))
ax.axis('off')# 标题
ax.set_title('Repartition of the world population')# 轴范围设置
lim = max(max(abs(circle.x) + circle.r,abs(circle.y) + circle.r,)for circle in circles
)
plt.xlim(-lim, lim)
plt.ylim(-lim, lim)# 绘制所有level=2的圆（各大洲）
for circle in circles:if circle.level != 2:continuex, y, r = circleax.add_patch( plt.Circle((x, y), r, alpha=0.5, linewidth=2, color="lightblue"))# 绘制level=3的圆（各大洲的各个国家），并标注国家名称
for circle in circles:if circle.level != 3:continuex, y, r = circlelabel = circle.ex["id"]ax.add_patch( plt.Circle((x, y), r, alpha=0.5, linewidth=2, color="#69b3a2"))plt.annotate(label, (x,y ), ha='center', color="white")# 为所有level=2的圆（各大洲）标注名称
for circle in circles:if circle.level != 2:continuex, y, r = circlelabel = circle.ex["id"]plt.annotate(label, (x,y ) ,va='center', ha='center', bbox=dict(facecolor='white', edgecolor='black', boxstyle='round', pad=.5))