python 词云 wordcloud

word_cloud 生成词云有两个方法。from text 和 from frequencies 。如果我们处理英文文档的话，就可以直接使用第一个方法，而不需要提前预处理文本，由于我们要做的是中文文本，所以我们必须自己分词，并处理为数组，使用第二种方法。

# -*- coding: utf-8 -*-


from os import path
from wordcloud import WordCloud

d = path.dirname(__file__)

# Read the whole text.
text = open(path.join(d, 'hua.txt')).read()
#frequencies = [(u'知乎',5),(u'小段同学',4),(u'曲小花',3),(u'中文分词',2),(u'样例',1)]

# Generate a word cloud image 此处原为 text 方法，我们改用 frequencies 
wordcloud = WordCloud().generate(text)
#wordcloud = WordCloud().fit_words(frequencies)

# Display the generated image:
# the matplotlib way:
import matplotlib.pyplot as plt
plt.imshow(wordcloud)
plt.axis("off")

# take relative word frequencies into account, lower max_font_size
wordcloud = WordCloud(max_font_size=40, relative_scaling=.5).generate(text)
#wordcloud = WordCloud(max_font_size=40, relative_scaling=.5).fit_words(frequencies)
plt.figure()
plt.imshow(wordcloud)
plt.axis("off")
plt.show()

# The pil way (if you don't have matplotlib)
#image = wordcloud.to_image()
#image.show()