pandas.DatetimeIndex.floor¶
-
DatetimeIndex.
floor
(self, *args, **kwargs)[source]¶ Perform floor operation on the data to the specified freq.
Parameters: - freq : str or Offset
The frequency level to floor the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end). See frequency aliases for a list of possible freq values.
- ambiguous : ‘infer’, bool-ndarray, ‘NaT’, default ‘raise’
Only relevant for DatetimeIndex:
- ‘infer’ will attempt to infer fall dst-transition hours based on order
- bool-ndarray where True signifies a DST time, False designates a non-DST time (note that this flag is only applicable for ambiguous times)
- ‘NaT’ will return NaT where there are ambiguous times
- ‘raise’ will raise an AmbiguousTimeError if there are ambiguous times
New in version 0.24.0.
- nonexistent : ‘shift_forward’, ‘shift_backward’, ‘NaT’, timedelta, default ‘raise’
A nonexistent time does not exist in a particular timezone where clocks moved forward due to DST.
- ‘shift_forward’ will shift the nonexistent time forward to the closest existing time
- ‘shift_backward’ will shift the nonexistent time backward to the closest existing time
- ‘NaT’ will return NaT where there are nonexistent times
- timedelta objects will shift nonexistent times by the timedelta
- ‘raise’ will raise an NonExistentTimeError if there are nonexistent times
New in version 0.24.0.
Returns: - DatetimeIndex, TimedeltaIndex, or Series
Index of the same type for a DatetimeIndex or TimedeltaIndex, or a Series with the same index for a Series.
Raises: - ValueError if the freq cannot be converted.
Examples
DatetimeIndex
>>> rng = pd.date_range('1/1/2018 11:59:00', periods=3, freq='min') >>> rng DatetimeIndex(['2018-01-01 11:59:00', '2018-01-01 12:00:00', '2018-01-01 12:01:00'], dtype='datetime64[ns]', freq='T') >>> rng.floor('H') DatetimeIndex(['2018-01-01 11:00:00', '2018-01-01 12:00:00', '2018-01-01 12:00:00'], dtype='datetime64[ns]', freq=None)
Series
>>> pd.Series(rng).dt.floor("H") 0 2018-01-01 11:00:00 1 2018-01-01 12:00:00 2 2018-01-01 12:00:00 dtype: datetime64[ns]