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Learn how to create a new column in a Pandas DataFrame based on whether one string column is a substring of another. Simple examples included!
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How to Check if Two String Columns Contain Each Other in Python using Pandas

In data processing and analysis, you often encounter situations where you need to compare different columns of strings in a DataFrame. One common requirement is to check if the value in one string column is a substring of another string column, or vice versa.

In this guide, we will address this problem using a simple dataset and demonstrate how to create a new column based on the comparison between two string columns.

Understanding the Problem

Let's consider the following dataset displayed as a Pandas DataFrame:

idab0lollolec1ramboram2kipio3ilocloc4striprstrip5lambdalambdaObjective

We want to create a new column c, which has the value 1 if:

Column a is equal to or a substring of column b, or

Column b is equal to or a substring of column a.

If neither condition is true, we will assign a value of 0 to column c.

The expected output should look like this:

idabc0lollolec11ramboram12kipio03ilocloc14striprstrip15lambdalambda1Solution Approaches

We can achieve this by using either zip and list comprehension or the apply method provided by Pandas.

1. Using Zip and List Comprehension

This method is clean and efficient. Here’s how to implement it:

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

In this code:

zip(df.a, df.b) pairs each element of column a with the corresponding element in column b.

The list comprehension checks both conditions (a in b or b in a), and converts the result into an integer (0 or 1).

Finally, we assign this list to the new column c.

2. Using the Apply Method

Alternatively, we can also use the apply method. Here's how:

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

In this example:

The apply function iterates over each row r of the DataFrame.

The lambda function checks if either string is in the other and again converts the result to an integer.

The axis=1 parameter indicates that we are applying the function to each row.

Final Result

Whichever method you choose, the output DataFrame will look like this:

idabc0lollolec11ramboram12kipio03ilocloc14striprstrip15lambdalambda1Conclusion

In this post, we covered how to check if two string columns in a Pandas DataFrame contain each other using Python. By leveraging list comprehension and the apply method, we created a new column to store the results of our comparisons effectively.

Feel free to apply these methods to your own data analysis projects, and enjoy your data wrangling with Pandas!