How to Perform Operations on Subset of Columns in Pandas DataFrames Using String Filtering

Learn how to efficiently perform operations on specific columns of your Pandas DataFrame identified by a string. This guide provides solutions to modify DataFrames based on column names containing certain keywords.
---

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Perform an operation on a subset of columns where column name contains string?

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Perform Operations on Subset of Columns in Pandas DataFrames Using String Filtering

Dealing with large datasets can be a daunting task, especially when the need arises to perform specific operations on certain columns based on their names. Have you ever found yourself in a situation where you need to modify specific columns in your Pandas DataFrame while keeping the rest of the data intact? If the column names include particular string patterns, you might wonder how to efficiently achieve this in Python using Pandas.

In this guide, we will explore a practical solution to a common problem: modifying a subset of columns in a DataFrame where the column names contain specific keywords. Let’s break down the solution step-by-step.

The Problem Statement

Assume you have two DataFrames, df1 and df2, which share identical columns. You want to create a new DataFrame by subtracting df2 from df1, followed by specific operations on certain columns based on their names. For instance, you might want to:

Multiply all columns containing "price_" by 100.

Divide all columns containing "spread_" by the corresponding values in df1.

Here’s an outline of what you initially consider for your code:

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

As you may have noticed, the approach above contains errors; however, the solution is relatively straightforward!

The Solution

Subtract the DataFrames: Start by subtracting df2 from df1 to create a new DataFrame, df_new.

Select and Modify Columns: Use loc to select the specific columns you want to edit based on the presence of certain strings in the column names.

Implementation Steps

Here’s the complete code you can use to implement this solution:

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

Explanation of the Code

df_new = df1 - df2: This line performs an element-wise operation to calculate the difference between the two DataFrames.

Conclusion