Having covered data loading, cleaning, and selection with Pandas, we now turn to a fundamental technique for data analysis: summarizing data by category. This chapter focuses on grouping operations.

You will work with the "split-apply-combine" approach, a common pattern for data aggregation. Specifically, you'll learn to:

• Use the groupby() method to segment DataFrames based on column values.
• Apply aggregation functions such as sum(), mean(), count(), min(), and max() to these segments.
• Perform multiple aggregations simultaneously using the .agg() method.
• Group data based on several columns to create hierarchical summaries.
• Access individual groups and their associated data after applying groupby().

By the end of this chapter, you will be able to effectively segment your data and calculate meaningful summary statistics for different groups within your DataFrames.