python 用 matplotlib 绘制 复合条饼图 实例详解

软件版本：

 

0、import

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.patches import ConnectionPatch

 

1、绘图

# 使图表元素中正常显示中文
mpl.rcParams['font.sans-serif'] = 'SimHei'
# 使坐标轴刻度标签正常显示负号
mpl.rcParams['axes.unicode_minus'] = False


# -------------------------------- 创建画布，划分子区 --------------------------------
fig = plt.figure(figsize=(12, 8),
                 facecolor='cornsilk'
                )
ax1, ax2 = fig.subplots(nrows=1,
                        ncols=2
                       )


# ------------------------------------- 绘制饼图 -------------------------------------
sales = [138, 181, 118, 107, 387]
labels = ['子', '丑', '寅', '卯', '其他']

# 
ax1.pie(x=sales,    # 数据
        autopct='%1.1f%%',    # 锲形块的数据标签格式
        startangle=70,    # 锲形块开始角度
        labels=labels,
        colors=cm.Blues(range(1, 300, 50)),
        explode=[0, 0, 0, 0, 0.05],    # 分裂距离
        textprops={'color': 'k',
                   'fontsize': 16},
       )

# ------------------------------------- 绘制条形图 -------------------------------------
sales = [98, 170, 119]
labels = ['甲', '乙', '丙']
colors = ['green', 'red', 'yellow']
xpos = 0 
bottom = 0

for j, _ in enumerate(sales):
    ration = sales[j]/sum(sales)
    ax2.bar(x=xpos,
            height=ration,
            width=0.5,
            bottom=bottom,
            color=colors[j]
           )
    ypos = bottom + ax2.patches[j].get_height() / 2
    bottom += ration    # 通过自增，实现堆积柱形的效果
    # 添加数据标签
    ax2.text(x=xpos,    # 标签文本的横轴坐标
             y=ypos,    # 竖轴坐标
             s='%s, %3.2f%%' % (labels[j], ax2.patches[j].get_height()),    # 标签的文本内容
             fontsize=16,
             ha='center',    # horizontal alignment
            )

ax2.axis('off')    # 关闭坐标轴

# 设置刻度范围
ax2.set_xlim(xmin=-0.6,
             xmax=1
　　　　　　  )

# ------------------------------------- 绘制连接线 -------------------------------------
# 获取锲形块的数据
theta1, theta2 = ax1.patches[-1].theta1, ax1.patches[-1].theta2
center, r = ax1.patches[-1].center, ax1.patches[-1].r
bar_height = sum([item.get_height() for item in ax2.patches])

# 上连接线
x = r * np.cos(np.pi / 180 * theta2) + center[0]
y = np.sin(np.pi / 180 * theta2) + center[1]
con1 = ConnectionPatch(xyA=(-width / 2, bar_height),
                      coordsA=ax2.transData,
                      xyB=(x, y),
                      coordsB=ax1.transData
                     )
# 下连接线
x = r * np.cos(np.pi / 180 * theta1) + center[0]
y = np.sin(np.pi / 180 * theta1) + center[1]
con2 = ConnectionPatch(xyA=(-width / 2, 0),
                      coordsA=ax2.transData,
                      xyB=(x, y), 
                      coordsB=ax1.transData
                     )
# 添加连接线
for con in [con1, con2]:
    con.set_color('gray')
    ax2.add_artist(con)
    con.set_linewidth(3)

    
# 调整子区布局
fig.subplots_adjust(wspace=0)


# 显示图形
plt.show()

图形：