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Counting Token in Paragraphs using Python
Ashish Katri
a year ago
Table of Contents
- How to count words Using nltk?
- How to count words using split function of python?
In this article, we will try to see how we
count the words in a paragraph using two different approaches.
Let’s take a text file which contains the
summary of a screenplay of a movie taken from Wikipedia and see how we can
perform the task.
Reading the File
FileName = ("script_file.txt")
with open(FileName, 'r') as file:
lines = file.read()
print(lines)Output
The format is structured so that one page equates to
roughly one minute of screen time, though this is only used as a ballpark
estimate and often bears little resemblance to the running time of the final
movie.[1] The standard font is 12 point, 10 pitch Courier Typeface.[2]
The major components are action (sometimes called
"screen direction") and dialogue. The action is written in the
present tense and is limited to what can be heard or seen by the audience, for
example descriptions of settings, character movements, or sound effects. The
dialogue is the words the characters speak, and is written in a center column.
Unique to the screenplay (as opposed to a stage play) is
the use of slug lines. A slug line, also called a master scene heading, occurs
at the start of every scene and typically contains three pieces of information:
whether the scene is set inside (interior/INT.) or outside (exterior/EXT.), the
specific location, and the time of day. Each slug line begins a new scene. In a
"shooting script" the slug lines are numbered consecutively for ease
of reference.How to count words Using nltk?
Here, we will see how we can use nltk package
to count the words in the given text file.
Let’s take an example
import nltk
FileName = ("script_file.txt")
with open(FileName, 'r') as file:
lines = file.read()
nltk_tokens = nltk.word_tokenize(lines)
print(nltk_tokens)
print("\n")
print("Number of Words: " ,len(nltk_tokens))Output:
['The', 'format', 'is', 'structured', 'so', 'that',
'one', 'page', 'equates', 'to', 'roughly', 'one', 'minute', 'of', 'screen', 'time',
',', 'though', 'this', 'is', 'only', 'used', 'as', 'a', 'ballpark', 'estimate',
'and', 'often', 'bears', 'little', 'resemblance', 'to', 'the', 'running',
'time', 'of', 'the', 'final', 'movie', '.', '[', '1', ']', 'The', 'standard',
'font', 'is', '12', 'point', ',', '10', 'pitch', 'Courier', 'Typeface', '.',
'[', '2', ']', 'The', 'major', 'components', 'are', 'action', '(', 'sometimes',
'called', '``', 'screen', 'direction', "''", ')', 'and', 'dialogue',
'.', 'The', 'action', 'is', 'written', 'in', 'the', 'present', 'tense', 'and',
'is', 'limited', 'to', 'what', 'can', 'be', 'heard', 'or', 'seen', 'by', 'the',
'audience', ',', 'for', 'example', 'descriptions', 'of', 'settings', ',',
'character', 'movements', ',', 'or', 'sound', 'effects', '.', 'The', 'dialogue',
'is', 'the', 'words', 'the', 'characters', 'speak', ',', 'and', 'is',
'written', 'in', 'a', 'center', 'column', '.', 'Unique', 'to', 'the',
'screenplay', '(', 'as', 'opposed', 'to', 'a', 'stage', 'play', ')', 'is',
'the', 'use', 'of', 'slug', 'lines', '.', 'A', 'slug', 'line', ',', 'also',
'called', 'a', 'master', 'scene', 'heading', ',', 'occurs', 'at', 'the',
'start', 'of', 'every', 'scene', 'and', 'typically', 'contains', 'three',
'pieces', 'of', 'information', ':', 'whether', 'the', 'scene', 'is', 'set',
'inside', '(', 'interior/INT', '.', ')', 'or', 'outside', '(', 'exterior/EXT',
'.', ')', ',', 'the', 'specific', 'location', ',', 'and', 'the', 'time', 'of',
'day', '.', 'Each', 'slug', 'line', 'begins', 'a', 'new', 'scene', '.', 'In',
'a', '``', 'shooting', 'script', "''", 'the', 'slug', 'lines', 'are',
'numbered', 'consecutively', 'for', 'ease', 'of', 'reference', '.']
Number of Words:
223How to count words using split function of python?
This is another approach to count numbers of
words in the given text file using python split() functions.
Let’s see it with an example
FileName = ("script_file.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()))Output:
['The', 'format', 'is', 'structured', 'so', 'that',
'one', 'page', 'equates', 'to', 'roughly', 'one', 'minute', 'of', 'screen',
'time,', 'though', 'this', 'is', 'only', 'used', 'as', 'a', 'ballpark',
'estimate', 'and', 'often', 'bears', 'little', 'resemblance', 'to', 'the',
'running', 'time', 'of', 'the', 'final', 'movie.[1]', 'The', 'standard',
'font', 'is', '12', 'point,', '10', 'pitch', 'Courier', 'Typeface.[2]', 'The',
'major', 'components', 'are', 'action', '(sometimes', 'called', '"screen',
'direction")', 'and', 'dialogue.', 'The', 'action', 'is', 'written', 'in',
'the', 'present', 'tense', 'and', 'is', 'limited', 'to', 'what', 'can', 'be',
'heard', 'or', 'seen', 'by', 'the', 'audience,', 'for', 'example',
'descriptions', 'of', 'settings,', 'character', 'movements,', 'or', 'sound',
'effects.', 'The', 'dialogue', 'is', 'the', 'words', 'the', 'characters',
'speak,', 'and', 'is', 'written', 'in', 'a', 'center', 'column.', 'Unique',
'to', 'the', 'screenplay', '(as', 'opposed', 'to', 'a', 'stage', 'play)', 'is',
'the', 'use', 'of', 'slug', 'lines.', 'A', 'slug', 'line,', 'also', 'called',
'a', 'master', 'scene', 'heading,', 'occurs', 'at', 'the', 'start', 'of', 'every',
'scene', 'and', 'typically', 'contains', 'three', 'pieces', 'of',
'information:', 'whether', 'the', 'scene', 'is', 'set', 'inside',
'(interior/INT.)', 'or', 'outside', '(exterior/EXT.),', 'the', 'specific',
'location,', 'and', 'the', 'time', 'of', 'day.', 'Each', 'slug', 'line',
'begins', 'a', 'new', 'scene.', 'In', 'a', '"shooting', 'script"',
'the', 'slug', 'lines', 'are', 'numbered', 'consecutively', 'for', 'ease',
'of', 'reference.']
Number of Words:
183I hope you enjoyed reading this article and finally, you came
to know about Counting Token in Paragraphs using Python.
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