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 than end_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

at_time

Select values at a particular time of the day.

first

Select initial periods of time series based on a date offset.

last

Select final periods of time series based on a date offset.

DatetimeIndex.indexer_between_time

Get just the index locations for values between particular times of the day.

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 than end_time:

>>> ts.between_time('0:45', '0:15')
                     A
2018-04-09 00:00:00  1
2018-04-12 01:00:00  4