I have 10 columns (dtype: datetime64). I want to remove the date and month from the columns and keep only the year.
10-01-1880 --> Would like to remove day and month
expecting --> 1880
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`df['column'].dt.year` – cs95 Apr 07 '19 at 06:55
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@coldspeed ... showing error df['year'].dt.year AttributeError: Can only use .dt accessor with datetimelike values – Jason Apr 07 '19 at 07:08
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From the observation, I can conclude that the type is indeed not `datetime64`. Please verify this information before posting next time... For now, you can do `pd.to_datetime(df['column'], errors='coerce').dt.year`. – cs95 Apr 07 '19 at 07:09
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@coldspeed... I have already converted my column using pd.to_datetime Name: year, dtype: datetime64[ns].. now I used your code... it showing l0 1970 1 1970 2 1970 3 1970 4 1970 5 1970 6 1970 7 1970 8 1970 9 1970 10 1970 11 1970 12 1970 13 1970 14 1970 15 1970 16 1970 Name: year, dtype: int64 – Jason Apr 07 '19 at 07:12
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@coldspeed.. I have column which has date-month-year for 25 rows.. I want to remove the date and month and keep the year.. – Jason Apr 07 '19 at 07:13
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You can't remove the date and month and still retain the type... the year is an integer, so you get a column of integers as a result. – cs95 Apr 07 '19 at 07:25
1 Answers
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This should do the trick. I am using datetime module https://docs.python.org/3/library/datetime.html
from datetime import datetime
#Convert string to datetime object
datetime_object = datetime.strptime('10-01-1880', '%d-%m-%Y')
#Extract year
print(datetime_object.day)
print(datetime_object.month)
print(datetime_object.year)
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#1880
Devesh Kumar Singh
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