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Python Pandas - How to perform ceil operation on the DateTimeIndex with specified frequency
To perform ceil operation on the DateTimeIndex with specified frequency, use the DateTimeIndex.ceil() method. For frequency, use the freq parameter.
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')Display DateTimeIndex −
print("DateTimeIndex...\n", datetimeindex)
Ceil operation on DateTimeIndex date with specified frequency −
print("\nPerforming ceil operation...\n",
datetimeindex.ceil(freq='us'))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 frequency
print("\nPerforming ceil operation...\n",
datetimeindex.ceil(freq='us'))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... DatetimeIndex(['2021-10-18 07:20:32.261812+10:30', '2021-10-18 07:21:12.261812+10:30', '2021-10-18 07:21:52.261812+10:30', '2021-10-18 07:22:32.261812+10:30', '2021-10-18 07:23:12.261812+10:30'], dtype='datetime64[ns, Australia/Adelaide]', freq=None)
Updated on: 19-Oct-2021
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