python中文分詞+詞頻統計的實現步驟

2022-06-11 18:00:30

前言

本文記錄了一下Python在文書處理時的一些過程+程式碼

一、文字彙入

我準備了一個名為abstract.txt的文字檔案

接著是在網上下載了stopword.txt(用於結巴分詞時的停用詞)

有一些是自己覺得沒有用加上去的

另外建立了自己的詞典extraDict.txt

準備工作做好了，就來看看怎麼使用吧！

二、使用步驟

1.引入庫

程式碼如下：

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

2.讀入資料

程式碼如下：

jieba.load_userdict('extraDict.txt')  # 匯入自己建立詞典

3.取出停用詞表

def stopwordlist():
    stopwords = [line.strip() for line in open('chinesestopwords.txt', encoding='UTF-8').readlines()]
    # ---停用詞補充,視具體情況而定---
    i = 0
    for i in range(19):
        stopwords.append(str(10 + i))
    # ----------------------
 
    return stopwords

4.分詞並去停用詞（此時可以直接利用python原有的函數進行詞頻統計）

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#統計每個詞出現的次數
    return  temp #顯示分詞結果
    #return str(sorted(counts.items(), key=lambda x: x[1], reverse=True)[:20])  # 統計出現前二十最多的詞及次數

5. 輸出分詞並去停用詞的有用的詞到txt

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

6.函數呼叫

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

7.結果

附：輸入一段話，統計每個字母出現的次數

先來講一下思路：

例如給出下面這樣一句話

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.

那麼想要統計裡面每一個單詞出現的次數，思路很簡單，遍歷一遍這個字串，再定義一個空字典count_dict，看每一個單詞在這個用於統計的空字典count_dict中的key中存在否，不存在則將這個單詞當做count_dict的鍵加入字典內，然後值就為1，若這個單詞在count_dict裡面已經存在，那就將它對應的鍵的值+1就行

下面來看程式碼：

#定義字串
sentences = """           # 字串很長時用三個引號
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.
"""
#具體實現
#  將句子裡面的逗號去掉,去掉多種符號時請用迴圈，這裡我就這樣吧
sentences=sentences.replace(',','')   
sentences=sentences.replace('.','')   #  將句子裡面的.去掉
sentences = sentences.split()         # 將句子分開為單個的單詞，分開後產生的是一個列表sentences
# print(sentences)
count_dict = {}
for sentence in sentences:
    if sentence not in count_dict:    # 判斷是否不在統計的字典中
        count_dict[sentence] = 1
    else:                              # 判斷是否不在統計的字典中
        count_dict[sentence] += 1
for key,value in count_dict.items():
    print(f"{key}出現了{value}次")

輸出結果是這樣：