pytho机器学习入门之WordCloud的使用(词云，文字云)

词云（wordcloud）也叫文字云 是对文本中出现频率较高的关键词数据给予视觉差异化的展现方式，词云图突出展示高频高质的信息，也能过滤大部分低频的文本，利用词云，可以通过可视化形式凸显数据所体现的主旨，快速显示数据中各种文本信息的频率

from sklearn.datasets import load_iris
from sklearn.datasets import load_boston
import pandas as pd
import pylab
import matplotlib; matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from imageio import imread
import numpy as np
f=open(r'zhangsan.txt').read()
bgpic=imread(r'C:\Users\Admin\Desktop\test.jpg')

wdcd=WordCloud(mask=bgpic,background_color="white",scale=1.5)
wdcd=wdcd.generate(f)
plt.imshow(wdcd)

#wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2).generate(f)
#plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wdcd.to_file('pic.jpg')
pylab.show()
#wordcloud.to_file('1.png')

同样可以自行设置过滤的词

效果如下

 代码如下 测试文件可以自己编写 输入想要的字符

from sklearn.datasets import load_iris
from sklearn.datasets import load_boston
import pandas as pd
import pylab
import matplotlib; matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from imageio import imread
import numpy as np
f=open(r'zhangsan.txt').read()
bgpic=imread(r'C:\Users\Admin\Desktop\test.jpg')

wdcd=WordCloud(mask=bgpic,background_color="white",scale=1.5)
wdcd=wdcd.generate(f)
plt.imshow(wdcd)

#wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2).generate(f)
#plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wdcd.to_file('pic.jpg')
pylab.show()
#wordcloud.to_file('1.png')