Python Text Processing 简明教程

Python - Counting Token in Paragraphs

当从源文本中读取文本时，有时我们还需要了解关于所用单词类型的一些统计信息。这就需要统计特定类型单词的数量和行数。在以下示例中，我们展示了使用两种不同方法统计段落中单词数量的程序。为此，我们考虑包含好莱坞电影概要的一个文本文件。

Reading the File

FileName = ("Path\GodFather.txt")

with open(FileName, 'r') as file:
    lines_in_file = file.read()
    print lines_in_file

当我们运行以上程序时，我们得到了以下输出 −

Vito Corleone is the aging don (head) of the Corleone Mafia Family. His youngest son Michael has returned from WWII just in time to see the wedding of Connie Corleone (Michael's sister) to Carlo Rizzi. All of Michael's family is involved with the Mafia, but Michael just wants to live a normal life. Drug dealer Virgil Sollozzo is looking for Mafia families to offer him protection in exchange for a profit of the drug money. He approaches Don Corleone about it, but, much against the advice of the Don's lawyer Tom Hagen, the Don is morally against the use of drugs, and turns down the offer. This does not please Sollozzo, who has the Don shot down by some of his hit men. The Don barely survives, which leads his son Michael to begin a violent mob war against Sollozzo and tears the Corleone family apart.

Counting Words Using nltk

接下来，我们使用 nltk 模块统计文本中的单词数量。请注意单词“（head）”被计为 3 个单词，而不是 1 个。

import nltk

FileName = ("Path\GodFather.txt")

with open(FileName, 'r') as file:
    lines_in_file = file.read()

    nltk_tokens = nltk.word_tokenize(lines_in_file)
    print nltk_tokens
    print "\n"
    print "Number of Words: " , len(nltk_tokens)

当我们运行以上程序时，我们得到了以下输出 −

['Vito', 'Corleone', 'is', 'the', 'aging', 'don', '(', 'head', ')', 'of', 'the', 'Corleone', 'Mafia', 'Family', '.', 'His', 'youngest', 'son', 'Michael', 'has', 'returned', 'from', 'WWII', 'just', 'in', 'time', 'to', 'see', 'the', 'wedding', 'of', 'Connie', 'Corleone', '(', 'Michael', "'s", 'sister', ')', 'to', 'Carlo', 'Rizzi', '.', 'All', 'of', 'Michael', "'s", 'family', 'is', 'involved', 'with', 'the', 'Mafia', ',', 'but', 'Michael', 'just', 'wants', 'to', 'live', 'a', 'normal', 'life', '.', 'Drug', 'dealer', 'Virgil', 'Sollozzo', 'is', 'looking', 'for', 'Mafia', 'families', 'to', 'offer', 'him', 'protection', 'in', 'exchange', 'for', 'a', 'profit', 'of', 'the', 'drug', 'money', '.', 'He', 'approaches', 'Don', 'Corleone', 'about', 'it', ',', 'but', ',', 'much', 'against', 'the', 'advice', 'of', 'the', 'Don', "'s", 'lawyer', 'Tom', 'Hagen', ',', 'the', 'Don', 'is', 'morally', 'against', 'the', 'use', 'of', 'drugs', ',', 'and', 'turns', 'down', 'the', 'offer', '.', 'This', 'does', 'not', 'please', 'Sollozzo', ',', 'who', 'has', 'the', 'Don', 'shot', 'down', 'by', 'some', 'of', 'his', 'hit', 'men', '.', 'The', 'Don', 'barely', 'survives', ',', 'which', 'leads', 'his', 'son', 'Michael', 'to', 'begin', 'a', 'violent', 'mob', 'war', 'against', 'Sollozzo', 'and', 'tears', 'the', 'Corleone', 'family', 'apart', '.']

Number of Words:  167

Counting Words Using Split

接下来，我们使用 Split 函数统计单词数量，这里单词“（head）”被计为一个单词，而不是像使用 nltk 时统计为 3 个单词。

FileName = ("Path\GodFather.txt")

with open(FileName, 'r') as file:
    lines_in_file = file.read()

    print lines_in_file.split()
    print "\n"
    print  "Number of Words: ", len(lines_in_file.split())

当我们运行以上程序时，我们得到了以下输出 −

['Vito', 'Corleone', 'is', 'the', 'aging', 'don', '(head)', 'of', 'the', 'Corleone', 'Mafia', 'Family.', 'His', 'youngest', 'son', 'Michael', 'has', 'returned', 'from', 'WWII', 'just', 'in', 'time', 'to', 'see', 'the', 'wedding', 'of', 'Connie', 'Corleone', "(Michael's", 'sister)', 'to', 'Carlo', 'Rizzi.', 'All', 'of', "Michael's", 'family', 'is', 'involved', 'with', 'the', 'Mafia,', 'but', 'Michael', 'just', 'wants', 'to', 'live', 'a', 'normal', 'life.', 'Drug', 'dealer', 'Virgil', 'Sollozzo', 'is', 'looking', 'for', 'Mafia', 'families', 'to', 'offer', 'him', 'protection', 'in', 'exchange', 'for', 'a', 'profit', 'of', 'the', 'drug', 'money.', 'He', 'approaches', 'Don', 'Corleone', 'about', 'it,', 'but,', 'much', 'against', 'the', 'advice', 'of', 'the', "Don's", 'lawyer', 'Tom', 'Hagen,', 'the', 'Don', 'is', 'morally', 'against', 'the', 'use', 'of', 'drugs,', 'and', 'turns', 'down', 'the', 'offer.', 'This', 'does', 'not', 'please', 'Sollozzo,', 'who', 'has', 'the', 'Don', 'shot', 'down', 'by', 'some', 'of', 'his', 'hit', 'men.', 'The', 'Don', 'barely', 'survives,', 'which', 'leads', 'his', 'son', 'Michael', 'to', 'begin', 'a', 'violent', 'mob', 'war', 'against', 'Sollozzo', 'and', 'tears', 'the', 'Corleone', 'family', 'apart.']

Number of Words:  146