How to Append Column Values Based on String Conditions in Pandas DataFrames

Learn how to efficiently append values from one DataFrame to another based on string conditions using Python's Pandas library.
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How to Append Column Values Based on String Conditions in Pandas DataFrames

Manipulating data effectively is a core skill in data science and analytics, particularly when working with data in Python’s powerful Pandas library. One common problem that DataFrame users face is appending new column values based on whether specific strings in one column match or contain strings from another DataFrame. In this guide, we’ll guide you through a practical approach to solving this problem with detailed explanations and code snippets.

The Problem

Imagine you have two DataFrames: df and df2. In df, you have a column b containing strings, and in df2, there's a column b2 with other strings. Your task is to create a new column a3 in df, which appends values from column a2 of df2 if any of the strings in column b of df contain the strings in column b2. Let's clarify this with an example.

Example DataFrames

DataFrame df:

ab1100abc2300dfgDataFrame df2:

a2b21L1bc2L2op3L3fgDesired Output:

Your goal is to have the following DataFrame after processing:

aba31100abcL12300dfgL3Now, let’s dive into how to achieve this using Pandas.

The Solution

Create a Boolean DataFrame: We will generate a DataFrame containing boolean values indicating whether each string in b contains any string in b2.

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

Join with the original DataFrame: After identifying matches, we can join this common DataFrame back to our original DataFrame df.

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

Final DataFrame: You will end up with a DataFrame containing the desired new column:

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

This output shows the new column a3 successfully appended to df, corresponding to the conditions provided.

Conclusion

Happy coding! If you found this post helpful, feel free to share it or comment with your thoughts and experiences!