Solution to matplotlib Chinese garbled characters in Python-Python Tutorial-php.cn

Matplotlib is a goodplottingpackage forPython, but it does not support Chinese itself (it seems that there is no Chinese font in its default configuration), so if it appears in the drawing Chinese, garbled characters will appear

Matplotlib is a good drawing package for Python, but it does not support Chinese (it seems that there is no Chinese font in its default configuration), so if Chinese appears in the drawing, it will Garbled characters will appear.

When matplotlib draws images with Chinese annotations, there will begarbled characters.

Example code:

import matplotlib import matplotlib.pyplot as plt #定义文本框和箭头格式 decisionNode =dict(boxstyle="sawtooth",fc="0.8") leafNode=dict(boxstyle="round4",fc="0.8") arrow_args=dict(arrowstyle="<-") #绘制带箭头的注解 def plotNode(nodeTxt,centerPt,parentPt,nodeType): createPlot.axl.annotate(nodeTxt,xy=parentPt,xycoords='axes fraction',xytext=centerPt,textcoords='axes fraction',va="center",ha="center",bbox=nodeType,arrowprops=arrow_args) def createPlot(): fig =plt.figure(1,facecolor='white') fig.clf() createPlot.axl=plt.subplot(111,frameon=False) plotNode(U'决策点',(0.5,0.1),(0.1,0.5),decisionNode) plotNode(U'叶节点',(0.8,0.1),(0.3,0.8),leafNode) plt.show()

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Solution: Introduce font

import matplotlib.pyplot as plt import matplotlib #定义自定义字体，文件名是系统中文字体 myfont = matplotlib.font_manager.FontProperties(fname='C:/Windows/Fonts/simkai.ttf') #解决负号'-'显示为方块的问题 matplotlib.rcParams['axes.unicode_minus']=False decisionNode =dict(boxstyle="sawtooth",fc="0.8") leafNode=dict(boxstyle="round4",fc="0.8") arrow_args=dict(arrowstyle="<-") def plotNode(nodeTxt,centerPt,parentPt,nodeType): createPlot.axl.annotate(nodeTxt,xy=parentPt,xycoords='axes fraction',xytext=centerPt,textcoords='axes fraction',va="center",ha="center",bbox=nodeType,arrowprops=arrow_args,fontproperties=myfont) def createPlot(): fig =plt.figure(1,facecolor='white') fig.clf() createPlot.axl=plt.subplot(111,frameon=False) plotNode(U'决策点',(0.5,0.1),(0.1,0.5),decisionNode) plotNode(U'叶节点',(0.8,0.1),(0.3,0.8),leafNode) plt.show()

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