Grouping data

One typical workflow during data exploration looks as follows:

• You find a criterion that you want to use to group your data. Maybe you have GDP data for every country along with the continent and you would like to ask questions about the continents. These questions usually lead to some function applications- you might want to compute the mean GDP per continent. Finally, you want to store this data for further processing in a new data structure.

• We use a simpler example here. Imagine some fictional weather data about the number of sunny hours per day and city:

  >>> df
            date    city  value
  0   2000-01-03  London      6
  1   2000-01-04  London      3
  2   2000-01-05  London      4
  3   2000-01-03  Mexico      3
  4   2000-01-04  Mexico      9
  5   2000-01-05  Mexico      8
  6   2000-01-03  Mumbai     12
  7   2000-01-04  Mumbai      9
  8   2000-01-05  Mumbai      8
  9   2000-01-03   Tokyo      5
  10  2000-01-04   Tokyo      5
  11  2000-01-05   Tokyo      6
  

• The groups attributes...