BPt.Dataset.between_time#
- Dataset.between_time(start_time, end_time, include_start=_NoDefault.no_default, include_end=_NoDefault.no_default, inclusive=None, axis=None)[source]#
Select values between particular times of the day (e.g., 9:00-9:30 AM).
By setting
start_time
to be later thanend_time
, you can get the times that are not between the two times.- Parameters
- start_timedatetime.time or str
Initial time as a time filter limit.
- end_timedatetime.time or str
End time as a time filter limit.
- include_startbool, default True
Whether the start time needs to be included in the result.
Deprecated since version 1.4.0: Arguments include_start and include_end have been deprecated to standardize boundary inputs. Use inclusive instead, to set each bound as closed or open.
- include_endbool, default True
Whether the end time needs to be included in the result.
Deprecated since version 1.4.0: Arguments include_start and include_end have been deprecated to standardize boundary inputs. Use inclusive instead, to set each bound as closed or open.
- inclusive{“both”, “neither”, “left”, “right”}, default “both”
Include boundaries; whether to set each bound as closed or open.
- axis{0 or ‘index’, 1 or ‘columns’}, default 0
Determine range time on index or columns value. For Series this parameter is unused and defaults to 0.
- Returns
- Series or DataFrame
Data from the original object filtered to the specified dates range.
- Raises
- TypeError
If the index is not a
DatetimeIndex
See also
Examples
>>> i = pd.date_range('2018-04-09', periods=4, freq='1D20min') >>> ts = pd.DataFrame({'A': [1, 2, 3, 4]}, index=i) >>> ts A 2018-04-09 00:00:00 1 2018-04-10 00:20:00 2 2018-04-11 00:40:00 3 2018-04-12 01:00:00 4
>>> ts.between_time('0:15', '0:45') A 2018-04-10 00:20:00 2 2018-04-11 00:40:00 3
You get the times that are not between two times by setting
start_time
later thanend_time
:>>> ts.between_time('0:45', '0:15') A 2018-04-09 00:00:00 1 2018-04-12 01:00:00 4