Python词云生成并保存（jieba+WordCloud） 详解Python数据可视化编程 - 词云生成并保存（jieba+WordCloud）

# -*- coding: utf-8 -*-
"""
Created on Tue Mar 5 17:59:29 2019
@author: dell
"""
 
 
# =============================================================================
# 步骤：
# 分割aaa = jieba.cut(str,cut_all=True/False)
# 连接bbb = " ".join(aaa)
# 制作xxx = WordCloud(background_color,font_path).generate(bbb)  #bbb为字符串
# 显示plt.imshow(xxx)  #不能用plt.show()
# 取消坐标轴的显示Matplotlib.pyplot.axis("off")
# 存为图片xxx.to_file(path)
# =============================================================================
 
 
 
from wordcloud import WordCloud
from matplotlib import pyplot as plt
import jieba
 
with open("pythonTest.txt",encoding="utf-8") as f:
  text = f.read()
#textFromFile = open("pythonTest",encoding = "UTF-8").read()
 
 
word_list = jieba.cut("ABVDEFG",cut_all=True)  #切成了一个个的字符串
xxx = " ".join(word_list)  #"分隔符".join(需要被连接的数据) 将内容连接为字符串
 
myWordCloud = WordCloud(background_color="white",font_path='C:\windows\Fonts\STZHONGS.TTF').generate(text)
#myWordCloud = WordCloud(background_color="white",width=1000,height=860,font_path='C:\windows\Fonts\STZHONGS.TTF').generate(text)
plt.axis("off")
#plt.show(myWordCloud)  #没有实际显示，只有背景！！！
plt.imshow(myWordCloud)
 
myWordCloud.to_file("词云图片.jpg")  #保存为图片
 

import jieba
wordList = jieba.cut("机器学习,算法对新鲜样本!的适应能力：叫泛化能力",cut_all=False)
print(type(wordList))  #类型是一个生成器generator
print(wordList)    #本身是一个生成器对象generator Object
for list in wordList:
  if list in ",./;'[]~!@#$%^&*()_+，。、；‘ 【】~！@#￥%……&*（）——+《 》？：“{}<>?:\n\r":
    None
  else:
    print(list)