python中文分词+词频统计的实现步骤

import jieba
from jieba.analyse import extract_tags
from sklearn.feature_extraction.text import TfidfVectorizer

jieba.load_userdict('extraDict.txt')  # 导入自己建立词典

def stopwordlist():
    stopwords = [line.strip() for line in open('chinesestopwords.txt', encoding='UTF-8').readlines()]
    # ---停用词补充,视具体情况而定---
    i = 0
    for i in range(19):
        stopwords.append(str(10 + i))
    # ----------------------
 
    return stopwords

def seg_word(line):
    # seg=jieba.cut_for_search(line.strip())
    seg = jieba.cut(line.strip())
    temp = ""
    counts = {}
    wordstop = stopwordlist()
    for word in seg:
        if word not in wordstop:
            if word != ' ':
                temp += word
                temp += '\n'
                counts[word] = counts.get(word, 0) + 1#统计每个词出现的次数
    return  temp #显示分词结果
    #return str(sorted(counts.items(), key=lambda x: x[1], reverse=True)[:20])  # 统计出现前二十最多的词及次数

def output(inputfilename, outputfilename):
    inputfile = open(inputfilename, encoding='UTF-8', mode='r')
    outputfile = open(outputfilename, encoding='UTF-8', mode='w')
    for line in inputfile.readlines():
        line_seg = seg_word(line)
        outputfile.write(line_seg)
    inputfile.close()
    outputfile.close()
    return outputfile

if __name__ == '__main__':
    print("__name__", __name__)
    inputfilename = 'abstract.txt'
    outputfilename = 'a1.txt'
    output(inputfilename, outputfilename)

#定义字符串
sentences = """           # 字符串很长时用三个引号
Love is more than a word
it says so much.
When I see these four letters,
I almost feel your touch.
This is only happened since
I fell in love with you.
Why this word does this,
I haven't got a clue.
"""
#具体实现
#  将句子里面的逗号去掉,去掉多种符号时请用循环，这里我就这样吧
sentences=sentences.replace(',','')   
sentences=sentences.replace('.','')   #  将句子里面的.去掉
sentences = sentences.split()         # 将句子分开为单个的单词，分开后产生的是一个列表sentences
# print(sentences)
count_dict = {}
for sentence in sentences:
    if sentence not in count_dict:    # 判断是否不在统计的字典中
        count_dict[sentence] = 1
    else:                              # 判断是否不在统计的字典中
        count_dict[sentence] += 1
for key,value in count_dict.items():
    print(f"{key}出现了{value}次")