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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')
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