Python 中英文词频统计，并制作词云。
# 英文词频
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# -*- coding: UTF-8 -*-
# Author: Vitan
with open('cp.txt','r') as f:
content = f.read()
# 清洗数据
import string
content = content.lower() # 格式化数据，转为小写
for i in string.punctuation: # 去除所有标点符号
content = content.replace(i, ' ')
wordList = content.split() # 切片分词
# 排除语法型词汇，代词、冠词、连词等无语义词
noMean = {'a','an','the','i','do','am','you','no','t','m','d','ve'}
wordSet = set(wordList) - noMean
wordList = list(wordSet)
# 统计单词数量
data = {}
for word in wordList:
#data[word] = data.get(word, 0) + 1
data[word] = wordList.count(word)
for key in data:
print(key,data[key],'次')
print("============")
# list.sort() 排序
wordList = list(data.items())
# 函数定义
'''
def takeSecond(elem): # 定义函数，获取每个单词的次数项
return elem[1]
wordList.sort(key = takeSecond,reverse = True)
'''
# 匿名函数
wordList.sort(key = lambda x:x[1],reverse = True)
print(wordList)
print("============")
# 排序
hist = []
for key, value in data.items():
hist.append([value, key])
hist.sort(reverse = True) # 降序
# 前20个
for i in range(20):
print(hist[i])
# 中文词频
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# -*- coding: UTF-8 -*-
# Author: Vitan
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud
# 读取文件内容
with open('ch.txt','r',encoding = 'UTF-8') as f:
content = f.read()
# 结巴分词
wordList = jieba.cut(content)
# 词频统计
data = {}
for word in wordList:
if len(word)==1:
continue
else:data[word]=data.get(word,0)+1
# 匿名函数获取每个单词的次数项统，降序
result = list(data.items())
result.sort(key=lambda x:x[1],reverse=True) # 排序
for i in range(20):
print(result[i])
# 设置词云
wordSplit = " ".join(dict(result))
wc = WordCloud(background_color="black", # 设置背景颜色
# mask = "图片", #设置背景图片
max_words=2000, # 设置最大显示的字数
# stopwords = "", #设置停用词
font_path="/usr/share/fonts/noto-cjk/NotoSansCJK-Medium.ttc",
# 设置中文字体，使得词云可以显示（词云默认字体是“DroidSansMono.ttf字体库”，不支持中文）
max_font_size=50, # 设置字体最大值
random_state=30, # 设置有多少种随机生成状态，即有多少种配色方案
)
mywc = wc.generate(wordSplit) # 生成词云
# 展示词云图
plt.imshow(mywc)
plt.axis("off")
plt.show()
wc.to_file('mywor.png') # 保存图片文件
1 | # -*- coding: UTF-8 -*- |
1 | # -*- coding: UTF-8 -*- |
