Data Have to year format 19 and 2019 how to convert it into a single format 2019

Question

I am cleaning some data working on Pandas and have one column year containing two formats of years 19 and 2019.

I am currently using pd.to_datetime(chelsea["Year"], format="%y")

it is giving me errors. Now how can I convert this column into a single format like 2019

ERROR is ValueError: unconverted data remains: 93

Answer 1

Have a look here: Handling multiple datetime formats with pd.to_datetime

In short, you can use errors=coerce to fill any years not matching a pattern with NaT. If you repeat that for all patterns you have in the data, you can then combine the different results together:

import pandas as pd

ser = pd.Series(["2019", "73", "2020", "01", "13", "1998", "99"])

one = pd.to_datetime(ser, format="%Y", errors="coerce")
two = pd.to_datetime(ser, format="%y", errors="coerce")

out = one.fillna(two)

out:

0   2019-01-01
1   1973-01-01
2   2020-01-01
3   2001-01-01
4   2013-01-01
5   1998-01-01
6   1999-01-01
dtype: datetime64[ns]

you can convert those back to just the year:

years = out.dt.strftime("%Y")