To perform floor operation on the DateTimeIndex with microseconds frequency, use the DateTimeIndex.floor() method. For microseconds frequency, use the freq parameter with value ‘us’.
At first, import the required libraries −
import pandas as pd
DatetimeIndex with period 7 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')Floor operation on DateTimeIndex date with microseconds frequency. For microseconds frequency, we have used 'us' −
print("\nPerforming floor operation with microseconds frequency...\n",
datetimeindex.floor(freq='us'))Example
Following is the code −
import pandas as pd
# DatetimeIndex with period 7 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)
# Floor operation on DateTimeIndex date with microseconds frequency
# For microseconds frequency, we have used 'us'
print("\nPerforming floor operation with microseconds frequency...\n",
datetimeindex.floor(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 floor operation with microseconds frequency... DatetimeIndex(['2021-10-18 07:20:32.261811+10:30', '2021-10-18 07:21:12.261811+10:30', '2021-10-18 07:21:52.261811+10:30', '2021-10-18 07:22:32.261811+10:30', '2021-10-18 07:23:12.261811+10:30'], dtype='datetime64[ns, Australia/Adelaide]', freq=None)