Converting column of floats to datetime

Question

I have a column of my dataframe that is made up of the following:

df['Year] = [2025, 2024, NaN, 2023, 2026, NaN] (these are type float64)

How can I convert these years to something in datetime format? Since there are no months or days included I feel like they have to output as [01-01-2025, 01-01-2021, NaT, 01-01-2023, 01-01-2026, NaT] by default.

But if there was a way to still have the column as [2025, 2024, NaT, 2023, 2026, NaT] then that would work well too.

Using df['Year'] = pd.DatetimeIndex(df['Year']).year just output [1970, 1970, NaN, 1970, 1970, NaN].

Thank you very much.

Asked By: user4740374

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Source

Answer 1

Probably not the most elegant solution but if you convert the column to string and fill the empty with a dummy year (say 1900) you can use parser from dateutil

from dateutil import parser

('01/01/'+df['year']).fillna('1900').apply(parser.parse)

Out[67]:

0   2025-01-01
1   2024-01-01
2   1900-07-21
3   2023-01-01
4   2026-01-01
5   1900-07-21

Answered By: Sean Meehan

Answer 2

You can use pandas’ to_datetime() and set errors='coerce' to take care of the NaNs (-> NaT)

df['Year'] = pd.to_datetime(df['Year'], format='%Y', errors='coerce')

The output is going to be like 01-01-2025, 01-01-2021 ...

Answered By: Ignatius Reilly

Converting column of floats to datetime

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