Exploring Pandas groupby functionality in Python

The Pandas groupby() function is a tool that allows you to split and organize data in a Pandas DataFrame into groups based on one or more columns. This is similar to the GROUP BY feature in SQL and other databases, which is used to group data based on certain criteria and perform aggregations on the resulting groups.

When you use the Pandas groupby() function, you can group your data by one or more columns and then perform various operations on the resulting groups, such as calculating summary statistics or applying transformations. This can be a useful way to analyze and understand your data in more depth.

Here is an example of how to use the groupby() function in Pandas:

You can also use the apply() function to apply a function to each group and combine the results into a new DataFrame. For example:

Furthermore, you can also use the agg() function to apply multiple functions to the grouped data at once. For example: