Python Pandas - How to perform ceil operation on the DateTimeIndex with milliseconds frequency

To perform ceil operation on the DateTimeIndex with milliseconds frequency, use the DateTimeIndex.ceil() method. For milliseconds frequency, use the freq parameter with value ‘ms’.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 5 and frequency as S i.e. seconds. The timezone is Australia/Adelaide −

datetimeindex = pd.date_range('2021-10-18 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='40S')

Ceil operation on DateTimeIndex date with milliseconds frequency. For milliseconds frequency, we have used 'ms' −

print("\nPerforming ceil operation with milliseconds frequency...\n",
datetimeindex.ceil(freq='ms'))

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 5 and frequency as S i.e. seconds
# timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-18 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='40S')

# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)

# display DateTimeIndex frequency
print("DateTimeIndex frequency...\n", datetimeindex.freq)

# Ceil operation on DateTimeIndex date with milliseconds frequency
# For milliseconds frequency, we have used 'ms'
print("\nPerforming ceil operation with milliseconds frequency...\n",
datetimeindex.ceil(freq='ms'))

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex(['2021-10-18 07:20:32.261811624+10:30',
'2021-10-18 07:21:12.261811624+10:30',
'2021-10-18 07:21:52.261811624+10:30',
'2021-10-18 07:22:32.261811624+10:30',
'2021-10-18 07:23:12.261811624+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='40S')
DateTimeIndex frequency...
<40 * Seconds>

Performing ceil operation with milliseconds frequency...
DatetimeIndex(['2021-10-18 07:20:32.262000+10:30',
'2021-10-18 07:21:12.262000+10:30',
'2021-10-18 07:21:52.262000+10:30',
'2021-10-18 07:22:32.262000+10:30',
'2021-10-18 07:23:12.262000+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq=None)