源码
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import jieba
from jieba.analyse import extract_tags
from collections import Counter
from wordcloud import WordCloud
import matplotlib.pyplot as plt
def stopwordslist(filepath):
stopwords = [line.strip() for line in open(filepath, 'r', encoding='utf-8').readlines()]
return stopwords
# 对句子去除停用词
def movestopwords(sentence):
stopwords = stopwordslist('lib/stop_words.txt') # 这里加载停用词的路径
outstr = ''
for word in sentence:
if word not in stopwords:
if word != '\t'and'\n':
outstr += word
# outstr += " "
return outstr
text = open('report.txt', 'r').read()
text = re.sub("[^\u4e00-\u9fa5]", "", text). # 中文的UTF8代码区间
filtered_content = movestopwords(text)
result = jieba.lcut(filtered_content)
count_array = Counter(result)
sorted(count_array.items())
common_c = count_array.most_common(100)
wc = WordCloud(
font_path="/Library/Fonts/Songti.ttc",
# 设置背景色
background_color='white',
# 允许最大词汇
max_words=200,
# 最大号字体
max_font_size=100,
)
wc.generate_from_frequencies(dict(common_c))
plt.figure()
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file('wordcloud.jpg')
停用词 stop_words.txt
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的
了
和
是
就
都
而
及
與
著
或
一個
沒有
我們
你們
妳們
他們
她們
是否
结果
踩过的坑
- WordCloud中一定要设定字体，否则会出现一堆框框