Time-series data in pandas can also be created to represent intervals of time other than daily frequency. Different frequencies can be generated with pd.date_range() by utilizing the freq parameter. This parameter defaults to a value of D, which represents daily frequency.
To introduce the creation of nondaily frequencies, the following command creates a DatetimeIndex with one-minute intervals using freq='T':
In [20]: bymin = pd.Series(np.arange(0, 90*60*24), pd.date_range('2014-08-01', '2014-10-29 23:59:00', freq='T')) bymin Out[20]: 2014-08-01 00:00:00 0 2014-08-01 00:01:00 1 2014-08-01 00:02:00 2 ... 2014-10-29 23:57:00 129597 2014-10-29 23:58:00 129598 2014-10-29 23:59:00 129599 Freq: T, dtype: int64
This time-series allows us to use forms of slicing at finer...