How to Rename Column Names in Pandas

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When you are working with data in Pandas, you may find that you need to rename the column names. This can be a quick and easy process if you know how to do it. In this blog post, we will show you how to rename column names in Pandas using two different methods. We will also give some tips on how to choose the best method for your needs.

How to Rename Column Names in Pandas using. rename ():

The first method for renaming column names in Pandas is to use the .rename() function. This function allows you to quickly and easily rename a column or columns in your dataframe. To use this function, you simply need to pass in the new name for the column as a string.

Here is an example:

In this example, we are renaming the “Age” column to “Age_Old”. Note that the “_” character is used to separate the old and new names for the column. This is a common convention when renaming columns.

Read More: How to replace characters in string Python

How to Rename Column Names in Pandas using. replace():

The second method for renaming column names in Pandas is to use the .replace() function. This function allows you to replace the values in a column with new values.

To use this function, you simply need to pass in the new column name as a string and the new values as a list.

Here is an example:

In this example, we are replacing the values in the “Age” column with new values.

  • We are using the .replace() function to do this, and we are passing in the “Age” column name and a list of new values.
  • The list of new values contains three items: “Adult”, “Teen”, and “Child”.
  • This will replace all of the old Age values with one of these new values.

Which Method Should I Use?

So, which method should you use when renaming column names in Pandas? Well, that depends on what you need to do. If you simply need to rename a column or columns, then the .rename() function is a good option. If you need to replace the values in a column with new values, then the .replace() function is a good option.

However, if you need to do more complex renaming tasks, such as replacing text with different text or performing string operations on the column names, then the .rename() function may not be suitable. In these cases, you may need to use the .replace() function instead.

Hopefully, this blog post has given you a good understanding of how to rename column names in Pandas. If you have any questions, please feel free to ask them in the comments section below. And be sure to check out our other posts on Pandas for more tips and tricks!

Read More: Get a List of Column Headers from a Pandas DataFrame

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