How To Tokenize A Column In Python

When working with text data in Python, tokenizing is an important data preprocessing step to make your data readable and usable by various algorithms. Tokenization involves converting a sequence of text into individual tokens or words. In this tutorial, you will learn how to tokenize a column in your dataset using Python.

This tutorial assumes you have a basic knowledge of Python and the Pandas library installed.

Step 1: Import Libraries and Load Data

First, import the Pandas library and read your dataset using the read_csv function. For this tutorial, we’ll use a sample dataset containing three text sentences in a CSV file. You can download the dataset here.

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import pandas as pd
 
data = pd.read_csv('sample_data.csv')
print(data)

The dataset should look like this:

                               ID       Sentence
1                           Hello   how are you?
2                I am doing great     thank you!
3  Python is an amazing language.            NaN
4    Data analysis is my passion.            NaN
5   Let's tokenize this sentence.            NaN

Step 2: Tokenize the Text Data in the Column

Now, let’s tokenize the sentences in the ‘Sentence’ column. We will use the Natural Language ToolKit (NLTK) library for this purpose. You can install the library with the following command:

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!pip install nltk

First, import the necessary functions from the NLTK library. Then, apply the word_tokenize function to the ‘Sentence’ column in the dataset.

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from nltk.tokenize import word_tokenize
 
data['tokenized_sentence'] = data['Sentence'].apply(word_tokenize)

You should now have an additional column in your dataset, ‘tokenized_sentence’, containing a list of tokens for each sentence.

Step 3: Verify the Results

Finally, let’s print out and verify the results to ensure that our tokenization has been performed correctly.

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print(data)

Your tokenized dataset should look like this:

                               ID       Sentence  tokenized_sentence
1                           Hello   how are you?  [how, are, you, ?]
2                I am doing great     thank you!     [thank, you, !]
3  Python is an amazing language.            nan               [nan]
4    Data analysis is my passion.            nan               [nan]
5   Let's tokenize this sentence.            nan               [nan]

Full Code

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import pandas as pd
from nltk.tokenize import word_tokenize
 
# Import dataset
data = pd.read_csv('sample_data.csv')
 
# Tokenize the text data in the column
data['tokenized_sentence'] = data['Sentence'].apply(word_tokenize)
 
# Verify the results
print(data)

Conclusion

In this tutorial, you’ve learned how to tokenize a column in Python using the Pandas and NLTK libraries.

This preprocessing step is crucial when working with text data to make it suitable for analysis by machine learning algorithms or natural language processing tasks.

Now that you have tokenized your dataset, you can move on to further processing and analysis!