For example, if creating the dataframe required querying a snowflake database. I have often seen people fall into this case if creating the dataframe is an expensive task. Not all the columns have to be renamed: df = df.rename(columns=, inplace=True)Īlternatively, there are cases where you want to preserve the original dataframe. So if the old variable name is old_var and the new variable name is new_var, you would present to the columns parameter as key/value pairs, inside of a dictionary: columns =, which is basically saying change the column name 'gross_domestic_product' to 'GDP'.Use the df.rename() function and refer the columns to be renamed. When you change column names using the rename method, you need to present the old column name and new column name inside of a Python dictionary. Let’s look carefully at how to use the columns parameter. Inside the parenthesis, you’ll use the columns parameter, which enables you to specify the columns that you want to change. Renaming a column or multiple columns in a Pandas dataframe is a very common task during that process and is quite straightforward to do using Pandas. You type the name of the dataframe, and then. When we use the rename method, we actually start with our dataframe. (The syntax for renaming columns and renaming rows labels is almost identical, but let’s just take it one step at a time.) Ok, let’s start with the syntax to rename columns. You can import pandas with the following code:Īnd if you need a refresher on Pandas dataframes and how to create them, you can read our tutorial on Pandas dataframes. A quick noteĮverything that I’m about to describe assumes that you’ve imported Pandas and that you already have a Pandas dataframe created. But again, it can also rename the row labels (i.e., the labels in the dataframe index). This technique is most often used to rename the columns of a dataframe (i.e., the variable names). Here, I’ll show you the syntax for how to rename Pandas columns, and also how to rename Pandas row labels. The Pandas rename method is fairly straight-forward: it enables you to rename the columns or rename the row labels of a Python dataframe. Ok, now that I’ve explained what the Pandas rename method does, let’s look at the syntax. I’ll show you examples of both of these in the examples section.īut first, let’s take a look at the syntax. The first method of renaming columns within. This technique is most often used to rename the columns of a dataframe (i.e., the variable names).īut again, it can also rename the row labels (i.e., the labels in the dataframe index). Pandas dataframe after renaming the columns during the loading of a csv file. The Pandas rename method is fairly straight-forward: it enables you to rename the columns or rename the row labels of a Python dataframe. Let’s start with a quick introduction to the rename method. If you need something specific, you can click on any of the following links. Parameters namelabel or list of labels Name (s) to set. Length of names must match number of levels in MultiIndex. I’ll explain what the technique does, how the syntax works, and I’ll show you clear examples of how to use it. pandas 2.0.0 documentation Index.rename(name, inplaceFalse) source Alter Index or MultiIndex name. In this tutorial, I’ll explain how to use the Pandas rename method to rename columns in a Python dataframe.
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