python - 如何在饼图中添加框和标签，如下图所示

Question

尝试创建一个与下图完全相同的图形，并希望将其保存为 jpeg。我有一个名为“custpref”的数据框，如下所示

tov_type            count
Inpatient               7
Office Visit            6
Appointment Schedule    1
Allergy Sheet           1

试过的代码如下： -

def addPieGraph():
# Create a list of colors (from iWantHue)
colors = ["#6287da","#72ac5c","#8653aa","#bb7438","#b94b75"]

# Create a pie chart
plt.pie(
    # using data total)arrests
    custpref['cnt'],
    # with the labels being officer names
    labels=custpref['tov_type'],
    # with no shadows
    shadow=False,
    # with colors
    colors=colors,
    # with the start angle at 90%
    startangle=90,
)

# View the plot drop above
plt.axis('equal')

# View the plot
plt.tight_layout()
plt.title("Top 5 Visit Types                  Total = 15 Visits")
plt.savefig(r"PieChart.png",bbox_inches="tight")
plt.show()

预期结果：- 饼图的预期外观

上面的代码绘制了饼图，只需要图例的帮助，指向它们的箭头，名称前面的计数和矩形框内的标签，图形周围有边框，如预期的输出。

（来自上述数据框和预期图形的图例可能会随着每个图形的变化而变化。我希望我的图形完全符合预期的图像所示。）

标签： pythonmatplotlib

Answer 1

注意：虽然它不是您目标的完美再现，但我认为它已经足够接近您，可以微调到您想要的结果。

我曾经gridspec创建两个单独的子图（pie_chart和title），添加了自定义注释行（改编自文档），并将子图格式化title为黑色，没有任何可见的刻度/刺。

绘图结果：

使用的完整代码：

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

custpref=pd.DataFrame({'tov_type':['Inpatient','Office Visit','Appointment Schedule','Allergy Sheet'],'count':[7,6,1,1]})

fig=plt.figure(figsize=(6,4))
gs1 = gridspec.GridSpec(1,1,
    left=0.1,right=0.7,
    bottom=0.1,top=0.7,
)
gs2 = gridspec.GridSpec(1,1,
    left=0.05,right=0.95,
    bottom=0.9,top=1.0,
)

pie_ax=fig.add_subplot(gs1[0])
title_ax=fig.add_subplot(gs2[0])

# Create a list of colors (from iWantHue)
colors = ["#6287da","#72ac5c","#8653aa","#bb7438","#b94b75"]

# Create a pie chart
wedges, texts = pie_ax.pie(
    # using data total)arrests
    custpref['count'],
    # with no shadows
    shadow=False,
    # with colors
    colors=colors,
    # with the start angle at 90%
    startangle=90,
)

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

for i, p in enumerate(wedges):
    ang = (p.theta2 - p.theta1)/2. + p.theta1
    y = np.sin(np.deg2rad(ang))
    x = np.cos(np.deg2rad(ang))
    horizontalalignment = {-1: "right", 1: "left"}[int(np.sign(x))]
    connectionstyle = "angle,angleA=0,angleB={}".format(ang)
    kw["arrowprops"].update({"connectionstyle": connectionstyle,"color":colors[i]})
    pie_ax.annotate(custpref['tov_type'][i], xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y),
                 horizontalalignment=horizontalalignment, **kw)

# View the plot drop above
pie_ax.axis('equal')


title_ax.set_facecolor('k')

title_ax.text(0.5,0.5,"Top 5 Visit Types                  Total = 15 Visits",
    ha="center",va="center",transform=title_ax.transAxes,color="w")

for side in ['top', 'bottom', 'left', 'right']:
    title_ax.spines[side].set_visible(False)
title_ax.axes.get_xaxis().set_visible(False)    
title_ax.axes.get_yaxis().set_visible(False)    


plt.savefig(r"PieChart.png",bbox_inches="tight")
plt.show()