Pandas Cookbook

How to do it...

1. Read in the flights dataset, and answer the first query by defining the grouping columns (AIRLINE, WEEKDAY), the aggregating column (CANCELLED), and the aggregating function (sum):

>>> flights.groupby(['AIRLINE', 'WEEKDAY'])['CANCELLED'] \           .agg('sum').head(7)AIRLINE  WEEKDAY
AA       1          41
         2           9
         3          16
         4          20
         5          18
         6          21
         7          29
Name: CANCELLED, dtype: int64

2. Answer the second query by using a list for each pair of grouping and aggregating columns. Also, use a list for the aggregating functions:

>>> flights.groupby(['AIRLINE', 'WEEKDAY']) \            ['CANCELLED', 'DIVERTED'].agg(['sum', 'mean']).head(7)

3. Answer the third query using a dictionary in ...