Python 如何向饼图添加框和标签，如下图所示

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

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

测试代码如下：-

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：-

上面的代码绘制饼图时，只需要使用图例、指向它们的箭头、名称前面的计数以及矩形框中的标签（图周围有边框）作为预期输出的帮助

（以上数据框和预期图中的手脚可能会随着每个图的变化而变化。我只希望我的图的外观如预期图所示。）

注意：虽然这并不是对目标的完美再现，但我认为这已经足够让你微调到期望的结果

我使用

gridspec

创建了两个独立的子图（

pie_-chart

和

title

），添加了自定义注释行（改编），并将

title

子图格式化为黑色，没有任何可见的记号/刺

绘图结果：

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()

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()

注意：虽然这不是对你的目标的完美再创造，但我认为这已经足够让你微调到你想要的结果

我使用

gridspec

创建了两个独立的子图（

pie_-chart

和

title

），添加了自定义注释行（改编），并将

title

子图格式化为黑色，没有任何可见的记号/刺

绘图结果：

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()

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()

---

这对我来说是可行的，但在某些情况下，我会遇到错误“给定的线不相交。请验证角度不相等或相差180度。”有解决方案吗？@P.Natu-Hmm，由于使用了

紧密布局（）

，这似乎是matplotlib 3.x中的一个错误；如果您导入matplotlib，您的打印内容是什么（matplotlib.\uuuu版本）？它是3.0.3。我也尝试了不同的开始角度。在这种情况下，设置startangle=-40有效。在其他此类情况下，它是否有效。。这对我来说是可行的，但在某些情况下，我会遇到错误“给定的线不相交。请验证角度不相等或相差180度。”有解决方案吗？@P.Natu-Hmm，由于使用了

紧密布局（）

，这似乎是matplotlib 3.x中的一个错误；如果您导入matplotlib，您的打印内容是什么（matplotlib.\uuuu版本）？它是3.0.3。我也尝试了不同的开始角度。在这种情况下，设置startangle=-40有效。在其他此类情况下，它是否有效。。