#加载自定义字典jieba.load_userdict("newdic.txt)

获取关键词

# jieba.cut 生成generator

# 全模式分词

seg_list = jieba.cut("我来北京上学", cut_all=True)

print("Full Model " + '/'.join(seg_list))

# 精确模式 （默认）

seg_list = jieba.cut("我来北京上学", cut_all=False)

# jieba.lcut 生成List

tags = jieba.lcut(text)

tags_df = pd.DataFrame({'segment': tags})

# 去除停用词

stopword = pd.read_csv("stopwords.txt", header=None, names=['words'], encoding='utf-8')

tags_df = tags_df[~tags_df['segment'].isin(stopword.words)]

print(tags_df)

正则表达式取中文字符

pattern = re.compile(r'[\u4e00-\u9fa5]+')

filter_data = re.findall(pattern, text)

text = ''.join(filter_data)

print(text)

# 获取关键词

# tags = jieba.analyse.extract_tags(text, topK=3)

# jieba.lcut 生成List

tags = jieba.lcut(text)

tags_df = pd.DataFrame({'segment': tags})

# 去除停用词

stopword = pd.read_csv("stopwords.txt", header=None, names=['words'], encoding='utf-8')

tags_df = tags_df[~tags_df['segment'].isin(stopword.words)]

# tags_df.index =

print(tags_df)

# 词频计数

word_count = tags_df.groupby('segment')['segment'].count().sort_values(ascending=False)

print(word_count[:5])