Python Pandas - Extract the microseconds from the DateTimeIndex with specific time series frequency


To extract the microsecond from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.microsecond property.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 6 and frequency as us i.e. microseconds. The timezone is Australia/Sydney −

datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='us')

Display DateTimeIndex −

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

Get the microsecond −

print("\nGetting the microseconds..\n",datetimeindex.microsecond)

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 6 and frequency as us i.e. microseconds
# The timezone is Australia/Sydney
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='us')

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

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

# get the microsecond
print("\nGetting the microseconds..\n",datetimeindex.microsecond)

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex([ '2021-10-20 02:30:50+11:00',
'2021-10-20 02:30:50.000001+11:00',
'2021-10-20 02:30:50.000002+11:00',
'2021-10-20 02:30:50.000003+11:00',
'2021-10-20 02:30:50.000004+11:00',
'2021-10-20 02:30:50.000005+11:00'],
dtype='datetime64[ns, Australia/Sydney]', freq='U')
DateTimeIndex frequency...
<Micro>

Getting the microseconds..
Int64Index([0, 1, 2, 3, 4, 5], dtype='int64')

Updated on: 18-Oct-2021

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