Pandas - Different time formats in the same column

Question

I have a Dataframe that has dates stored in different formats in the same column as shown below:

date
1-10-2018
2-10-2018
3-Oct-2018
4-10-2018

Answer 1

Use to_datetime with specify formats with errors='coerce' for replace not matched values to NaNs. Last combine_first for replace missing values by date2 Series.

date1 = pd.to_datetime(df['date'], format='%d-%m-%Y', errors='coerce')
date2 = pd.to_datetime(df['date'], format='%d-%b-%Y', errors='coerce')

df['date'] = date1.combine_first(date2)
print (df)
        date
0 2018-10-01
1 2018-10-02
2 2018-10-03
3 2018-10-04