How to Count Unique Words in Each Column Cell of a DataFrame in Python

Learn how to efficiently count unique words in each column cell of a DataFrame in Python using two effective methods.
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Counting Unique Words in Each Column Cell of a DataFrame in Python

Are you struggling to count unique words in each column cell of your DataFrame using Python? You’re not alone! This is a common challenge for many Python programmers working with data analysis in Pandas. Specifically, you may want to count each unique word while ignoring repeated occurrences of the same word within the same cell. In this guide, we’ll explore how to tackle this problem effectively with clear and straightforward solutions.

Problem Overview

Let’s consider an example to clarify the requirements. Suppose you have a DataFrame that contains reviews with sentences in one of its columns, like so:

1st: "I waited and waited and eventually left the hospital"

2nd: "I waited only 1 hour. My experience wasn't so bad"

You want to count the number of unique appearances for each word across all column cells, as follows:

waited: 2 (only counted once from each of the first and second cell)

hospital: 1

experience: 1

Solution

To solve this problem, we can utilize the Pandas library in Python. Below are two different methods you can implement to achieve the desired outcome. You can choose either based on your preferences or performance needs.

Method 1: Using set to Ensure Uniqueness

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Code:

apply() method: Applies a function along the DataFrame axis (each row in this case).

sum(axis = 0): Sums up the counts for each unique word across all cells.

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Code:

The rest of the code functions the same way as in the first method.

Performance Considerations

It is worth noting that both methods can perform similarly, but you may want to test them against your datasets to see which one runs faster or is more memory efficient. Depending on the size and characteristics of your data, the performance can vary.

Conclusion

Counting unique words in column cells of a DataFrame can be achieved effectively with either of the two methods detailed above. It’s an essential skill for text data processing in Python using the Pandas library. With these methods, you’ll be able to analyze text data more efficiently and extract valuable insights.

Feel free to experiment with these functions and adapt them as needed for your projects. Happy coding!