xorbits.pandas.DataFrame.between_time#

DataFrame.between_time(start_time, end_time, inclusive: IntervalClosedType = 'both', axis: Axis | None = None) → Self#

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_time (datetime.time or str) – Initial time as a time filter limit.

  • end_time (datetime.time or str) – End time as a time filter limit.

  • 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

Data from the original object filtered to the specified dates range.

Return type

Series or DataFrame

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

Warning

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.core.frame.DataFrame.