Pandas Series: between_time() function

Last update on September 15 2022 12:55:17 (UTC/GMT +8 hours)

Select values between particular times of the day

The between_time() function is used to select values at particular time of day (e.g. 10:30AM).

By setting start_time to be later than end_time, you can get the times that are not between the two times.

Syntax:

Series.between_time(self, start_time, end_time, include_start=True, include_end=True, axis=None)

Parameters:

Name	Description	Type/Default Value	Required / Optional
start_time		datetime.time or str	Required
end_time	For DataFrame, if not None, only use these columns to check for NaNs.	datetime.time or str	Required
include_start		bool Default Value: True	Required
include_end		bool Default Value: True	Required
axis		{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required

Returns: Series or DataFrame

Raises: TypeError
If the index is not a DatetimeIndex

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
i = pd.date_range('2019-04-09', periods=4, freq='1D20min')
ts = pd.DataFrame({'P': [2, 3, 4, 5]}, index=i)
ts

Output:

                      P
2019-04-09 00:00:00	2
2019-04-10 00:20:00	3
2019-04-11 00:40:00	4
2019-04-12 01:00:00	5

Python-Pandas Code:

import numpy as np
import pandas as pd
i = pd.date_range('2019-04-09', periods=4, freq='1D20min')
ts = pd.DataFrame({'P': [2, 3, 4, 5]}, index=i)
ts.between_time('0:15', '0:45')

Output:

                      P
2019-04-10 00:20:00	3
2019-04-11 00:40:00	4

Example - You get the times that are not between two times by setting start_time later than end_time:

Python-Pandas Code:

import numpy as np
import pandas as pd
i = pd.date_range('2019-04-09', periods=4, freq='1D20min')
ts = pd.DataFrame({'P': [2, 3, 4, 5]}, index=i)
ts.between_time('0:45', '0:15')

Output:

                      P
2019-04-09 00:00:00	2
2019-04-12 01:00:00	5

Previous: Select all the values in a row at the particular time of the day
Next: Series.dt.dayofweek() function