Python - Counting Token in Paragraphs





While reading the text from a source, sometimes we also need to find out some statistics about the type of words used. That makes it necessary to count the number of words as well as lines with a specific type of words in a given text. In the below example we show programs to count the words in a paragraph using two different approaches. We consider a text file for this purpose which contains the summary of a Hollywood movie.

Reading the File

FileName = ("Path\GodFather.txt")

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

When we run the above program we get the following output −

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

Next we use the nltk module to count the words in the text. Please note the word '(head)' is counted as 3 words and not one.

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)

When we run the above program we get the following output −

['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

Next we count the words using Split function and here the word '(head)' is counted as a single word and not 3 words as in case of using nltk.

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())

When we run the above program we get the following output −

['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


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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..
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Ans: Python Text Processing Tutorial for Beginners - Learn Python Text Processing in simple and easy steps starting from basic to advanced concepts with examples including Text Processing,Text Processing Environment,String Immutability,Sorting Lines,Reformatting Paragraphs,Counting Token in Paragraphs ,Convert Binary to ASCII,Convert ASCII to Binary,Strings as Files,Backward File Reading,Filter Duplicate Words,Extract Emails from Text,Extract URL from Text,Pretty Print Numbers,Text Processing State Machine,Capitalize and Translate,Tokenization,Remove Stopwords,Synonyms and Antonyms,Text Translation,Word Replacement,Spelling Check,WordNet Interface,Corpora Access,Tagging Words,Chunks and Chinks,Chunk Classification,Text Classification,Bigrams,Process PDF,Process Word Document,Reading RSS feed,Sentiment Analysis,Search and Match,Text Munging,Text wrapping,Frequency Distribution,Text Summarization,Stemming Algorithms,Constrained Search. view more..




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