The date I got from crawling is 22.01.16. If it comes out in this form and changes to date time, there is a bug that changes to an unexistent time. In this situation, how do I change the date to convert it correctly?
>>> import pandas as pd
>>> df = pd.DataFrame({"Date":[ "22.01.16", "22.01.15", "22.01.14", "22.01.13" ]})
>>> pd.to_datetime(df["Date"], format="%y.%m.%d")
0 2022-01-16
1 2022-01-15
2 2022-01-14
3 2022-01-13
Name: Date, dtype: datetime64[ns]
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 1 columns):
# # Column Non-Null Count Dtype
--- ------ -------------- -----
0 Date 4 non-null object
dtypes: object(1)
memory usage: 160.0+ bytes
>>> df["Date_datetime"] = pd.to_datetime(df["Date"], format="%y.%m.%d")
>>> df
Date Date_datetime
0 22.01.16 2022-01-16
1 22.01.15 2022-01-15
2 22.01.14 2022-01-14
3 22.01.13 2022-01-13
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 2 columns):
# # Column Non-Null Count Dtype
--- ------ -------------- -----
0 Date 4 non-null object
1 Date_datetime 4 non-null datetime64[ns]
dtypes: datetime64[ns](1), object(1)
memory usage: 192.0+ bytes
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