Replicating pivot_table with a groupby aggregation

At first glance, it may seem that the pivot_table method provides a unique way to analyze data. However, after a little massaging, it is possible to replicate its functionality exactly with a groupby aggregation. Knowing this equivalence can help shrink the universe of pandas functionality.

Getting ready

In this recipe, we use the flights dataset to create a pivot table and then recreate it using groupby operations.

How to do it...

1. Read in the flights dataset, and use the pivot_table method to find the total number of canceled flights per origin airport for each airline:

>>> flights = pd.read_csv('data/flights.csv')
>>> fp = flights.pivot_table(index='AIRLINE', 
                             columns='ORG_AIR', 
                             values='CANCELLED', 
                             aggfunc='sum',
                             fill_value=0).round(2)
>>> fp.head()

2. A groupby aggregation cannot directly replicate this...