Python 统计段落中的标记数

在阅读来自来源的文本时，有时我们也需要了解一些有关使用的词汇类型的统计信息。这使得在给定的文本中计算特定类型的单词数量以及行数成为必要。在下面的示例中，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。我们考虑一个文本文件，其中包含一部好莱坞电影的摘要。

读取文件

FileName = ("Path\GodFather.txt")

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

当我们运行上述程序时，我们会得到以下输出 –

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.

使用nltk计算单词数

接下来我们使用nltk模块来计算文本中的单词数。请注意单词”(head)”会计算为3个单词而不是一个。

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)

当我们运行上述程序时，我们会得到以下输出-

['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

使用Split函数计算单词数

接下来，我们使用Split函数来计算单词数，并且这里的单词”(head)”将被计算为一个单词，而不是像使用nltk时一样计算为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())

当我们运行上述程序时，我们会得到以下输出 –

['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