Find column whose name contains a specific string

📝 Tech Tips: How to Find a Column Name containing a Specific String in Python DataFrame

Are you stuck in finding a column in your Python DataFrame that contains a specific string? Don't worry! In this guide, I will show you easy solutions to this common problem.

💡 Problem Description

Let's say you have a DataFrame with multiple columns, and you need to find the column that contains a certain string. However, the column name may not exactly match the string. For example, you are searching for the string 'spike', but the column names could be like 'spike-2', 'hey spike', or 'spiked-in'. The only requirement is that the string 'spike' is continuous within the column name.

Additionally, you want the column name to be returned as a string or a variable, so you can access it later using df['name'] or df[name] as you normally would.

🛠️ Solution

To solve this problem, you can use Python's built-in string manipulation functions combined with the DataFrame's columns property. Here's a step-by-step solution:

1. Import the necessary modules:

   import pandas as pd import re

2. Create your DataFrame (assuming you already have one):

   df = pd.DataFrame({'spike-2': [1, 2, 3], 'hey spike': [4, 5, 6], 'spiked-in': [7, 8, 9]})

3. Use regular expressions (regex) to find the column name containing the desired string:

   string_to_find = 'spike' pattern = re.compile(f'.*{string_to_find}.*') matched_columns = [col for col in df.columns if pattern.match(col)]

4. Print the matched column names:

   for col in matched_columns: print(col)

   This will output:

   spike-2 hey spike spiked-in

5. Store the matched column name as a string or a variable for later use:

   # As a string matched_column_str = matched_columns[0] # Or as a variable matched_column_var = matched_columns[0]

   You can now access the matched column using df[matched_column_str] or df[matched_column_var].

📣 Call-to-Action

Now that you know how to find a column name containing a specific string in a Python DataFrame, go ahead and try it out in your own projects. If you have any questions or alternative solutions, leave a comment below and let's discuss!

Don't forget to share this article with your fellow Python enthusiasts who might find it helpful. Happy coding! 😄🐍