How to Split Pandas DataFrame into Multiple DataFrames by Column Value in Python

In this tutorial, I will show you how to create a separate DataFrame for each value for a given column.

Use the pandas.DataFrame.groupby(column) method to group the DataFrame by the values found in the column named column.

grouped_df = df.groupby('Column')

This method returns a GroupBy object. You can see this yourself by printing the new dataframe by running print grouped_df:

<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7efe3ec55670>

With the GroupBy object from the previous function, call the DataFrameGroupBy.get_group(group) method on the new dataframe grouped_df.

This method will return a Dataframe of all the rows that have the value group in the column named column.

grouped_df.get_group('column_value')

Alternatively, you can call both methods in one line:

value_df = df.groupby('Column').get_group('column_value')

Originally published at http://softwarenotebook.com on March 5, 2022.