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Learn how to easily reorder certain pandas columns while keeping all other columns intact, even in a large DataFrame with numerous columns.
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Reordering Pandas Columns Without Dropping Others

When working with data in Python, especially using the Pandas library, it's not uncommon to encounter situations where you need to reorder columns in your DataFrame. For those who have numerous columns, this task may seem daunting—especially if you want to maintain the integrity of all other columns while reordering just a few of them. In this guide, we will dive into a straightforward method to accomplish this without the hassle of manually specifying every column.

The Problem: Why Reorder Columns?

Imagine you have a DataFrame that contains several columns, but you want to rearrange a selected few for clarity or analysis purposes. For instance, your DataFrame initially appears like this:

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

And your goal is to reorder it into the following format:

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

However, instead of painstakingly writing out each column name—especially when dealing with hundreds of columns in a large DataFrame—there has to be an easier way to achieve this.

The Solution: Utilizing Sorted Function

Luckily, there's a simpler method to reorder your columns without needing to specify each individual name at all. By leveraging the sorted function in Python, you can effectively reorder the desired columns. Here's how you can do it:

Step-by-Step Instructions

Define Your Desired Column Order: Start by defining the columns you want to maintain at specific positions, like the Case column at the beginning and the Name column at the end.

Iterate and Sort Other Columns: Use the sorted function to ensure all columns between the designated ones are sorted alphabetically or in any order you desire.

Create a New DataFrame with the Reordered Columns: Finally, use this new order to reform your DataFrame.

Example Code

Here’s what the code looks like to achieve this:

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

Output Result

After executing the above code, your DataFrame should now appear like this:

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

Conclusion

Reordering columns in a Pandas DataFrame does not have to be a cumbersome task. By using the sorted function in Python, you can efficiently organize columns while still retaining your entire dataset intact. This method saves time and minimizes errors that often arise when managing larger sets of data, especially when the number of columns can reach up to 120 or more.

Now, whenever you find yourself needing to reorder specific columns while keeping others, remember this handy approach!