During the data analysis phase, categorizing a dataset into multiple categories or groups is often essential. We can do such categorization using the pandas library. The pandas groupby function is one of the most efficient and time-saving features for doing this. Groupby provides functionalities that allow us to split-apply-combine throughout the dataframe; that is, this function can be used for splitting, applying, and combining dataframes.
Similar to the Structured Query Language (SQL), we can use pandas and Python to execute more complex group operations by using any built-in functions that accept the pandas object or the numpy array.
In the next section, we are going to look into the groupby mechanics using the pandas library.
