Python for Finance: Analyze Big Financial Data

group_data.head()

Out[17]:                                                                                PRICE           IMP_VOL

                                    MATURITY            STRIKE

                                    2014-04-18  9                               8.85        2.083386

                                                                                10                          7.85        1.804194

                                                                                11                          6.85        1.550283

                                                                                12                          5.85        1.316103

                                                                                13                          4.85        1.097184

The resulting DataFrame object has two index levels and two columns. The following

shows all values that the two indices can take:

In  [ 18 ]: group_data.index.levels

Out[18]:    FrozenList([[2014-04-18 00:00:00,   2014-05-16  00:00:00,   2014-06-20  00:00

                                    :00,    2014-07-18  00:00:00,   2014-08-15  00:00:00,   2014-09-19  00:00:00,   201

                                    4-10-17 00:00:00,   2014-11-21  00:00:00],  [9.0,   10.0,   11.0,   12.0,   13.0,   1

                                    4.0,    15.0,   16.0,   17.0,   18.0,   19.0,   20.0,   21.0,   22.0,   23.0,   24.0,   25.0,

                                    26.0,   27.0,   28.0,   29.0,   30.0]])