pyspark.pandas.Series.between_time¶
- 
Series.between_time(start_time: Union[datetime.time, str], end_time: Union[datetime.time, str], include_start: bool = True, include_end: bool = True, axis: Union[int, str] = 0) → pyspark.pandas.series.Series[source]¶
- Select values between particular times of the day (example: 9:00-9:30 AM). - By setting - start_timeto 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 3.4.0. 
- include_endbool, default True
- Whether the end time needs to be included in the result. - Deprecated since version 3.4.0. 
- axis{0 or ‘index’, 1 or ‘columns’}, default 0
- Determine range time on index or columns value. 
 
- Returns
- Series
- 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. 
- 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 - >>> idx = pd.date_range('2018-04-09', periods=4, freq='1D20min') >>> psser = ps.Series([1, 2, 3, 4], index=idx) >>> psser 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 dtype: int64 - >>> psser.between_time('0:15', '0:45') 2018-04-10 00:20:00 2 2018-04-11 00:40:00 3 dtype: int64