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

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

At first, import the required libraries −

import pandas as pd

DatetimeIndex with period 6 and frequency as Y i.e. years. The timezone is Australia/Sydney −

datetimeindex = pd.date_range('2021-09-24 02:35:55', periods=6, tz='Australia/Sydney',freq='Y')

Display DateTimeIndex −

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

Get the year −

print("\nGetting the year name..\n",datetimeindex.year)

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 6 and frequency as Y i.e. years
# timezone is Australia/Sydney
datetimeindex = pd.date_range('2021-09-24 02:35:55', periods=6, tz='Australia/Sydney', freq='Y')

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

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

# get the year
print("\nGetting the year name..\n",datetimeindex.year)

Output

This will produce the following output −

DateTimeIndex...
DatetimeIndex(['2021-12-31 02:35:55+11:00', '2022-12-31 02:35:55+11:00',
               '2023-12-31 02:35:55+11:00', '2024-12-31 02:35:55+11:00',
               '2025-12-31 02:35:55+11:00', '2026-12-31 02:35:55+11:00'],
               dtype='datetime64[ns, Australia/Sydney]', freq='A-DEC')
DateTimeIndex frequency...
   <YearEnd: month=12>

Getting the year name..
   Int64Index([2021, 2022, 2023, 2024, 2025, 2026], dtype='int64')