Extract Year from DatetimeIndex in Python Pandas

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')