Numerical Computing with Python

How to do it...

1. Read in the flights dataset, and define the grouping columns (AIRLINE), aggregating columns (ARR_DELAY), and aggregating functions (mean):

>>> flights = pd.read_csv('data/flights.csv')>>> flights.head()

2. Place the grouping column in the groupby method and then call the agg method with a dictionary pairing the aggregating column with its aggregating function:

>>> flights.groupby('AIRLINE').agg({'ARR_DELAY':'mean'}).head()

3. Alternatively, you may place the aggregating column in the indexing operator and then pass the aggregating ...