Grouping in pandas involves dividing a DataFrame into groups based on the values in one or more columns. You can then apply a function to each group to compute a summary statistic, such as the mean, sum, or count.

To group a DataFrame in pandas, use the .groupby() method. This method accepts a column name or a list of column names and returns a groupby object.

Here is an example:

# Grouping by 'column_name' and calculating the mean of each group
grouped_data = df.groupby('column_name').mean()

This example demonstrates how to calculate the mean for each group formed based on the values in 'column_name'.