NLTK Tokenize: Create a list of words from a given string - w3resource
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NLTK Tokenize: Create a list of words from a given string

NLTK Tokenize: Exercise-3 with Solution

Write a Python NLTK program to create a list of words from a given string.

Sample Solution:

Python Code-1:

from nltk.tokenize import word_tokenize
text = "Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station."
print("\nOriginal string:")
print(text)
print("\nList of words:")
print(word_tokenize(text))

Sample Output:

Original string:
Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station.

List of words:
['Joe', 'waited', 'for', 'the', 'train', '.', 'The', 'train', 'was', 'late', '.', 'Mary', 'and', 'Samantha', 'took', 'the', 'bus', '.', 'I', 'looked', 'for', 'Mary', 'and', 'Samantha', 'at', 'the', 'bus', 'station', '.']

It's equivalent to the following code:

Python Code-2:

from nltk.tokenize import TreebankWordTokenizer
tokenizer = TreebankWordTokenizer()
text = "Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station."
print("\nOriginal string:")
print(text)
print("\nList of words:")
print(tokenizer.tokenize(text))

Output:

Original string:
Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station.

List of words:
['Joe', 'waited', 'for', 'the', 'train.', 'The', 'train', 'was', 'late.', 'Mary', 'and', 'Samantha', 'took', 'the', 'bus.', 'I', 'looked', 'for', 'Mary', 'and', 'Samantha', 'at', 'the', 'bus', 'station', '.']

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Previous: Write a Python NLTK program to tokenize sentences in languages other than English.
Next: Write a Python NLTK program to split all punctuation into separate tokens.

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Python: Tips of the Day

Get the Key Whose Value Is Maximal in a Dictionary:

>>> model_scores = {'model_a': 100, 'model_z': 198, 'model_t': 150}
>>> # workaround
>>> keys, values = list(model_scores.keys()), list(model_scores.values())
>>> keys[values.index(max(values))]
'model_z'
>>> # one-line
>>> max(model_scores, key=model_scores.get)
'model_z'