Grouping and aggregating with multiple columns and functions
It is possible to do grouping and aggregating with multiple columns. The syntax is only slightly different than it is for grouping and aggregating with a single column. As usual with any kind of grouping operation, it helps to identify the three components: the grouping columns, aggregating columns, and aggregating functions.
Getting ready
In this recipe, we showcase the flexibility of the groupby DataFrame method by answering the following queries:
- Finding the number of cancelled flights for every airline per weekday
- Finding the number and percentage of cancelled and diverted flights for every airline per weekday
- For each origin and destination, finding the total number of flights, the number and percentage of cancelled flights, and the average and variance of the airtime
How to do it...
- Read in the flights dataset, and answer the first query by defining the grouping columns (
AIRLINE, WEEKDAY), the aggregating column (CANCELLED), and...
