How to make two different date format in single column unique?

Question

I have one column in I don\'t understand how but there is two different format in a single column.

df[\'Date\'] = [6/24/2019,6/14/2019,2019-09-06 00:00:00,6/         


        

Answer 1

Try importing the datetime class. This will allow you to use the strptime function like below:

format = '%d/%m/%Y'
data['New_date'] = datetime.strptime('2019-09-06 00:00:00', format)

Answer 2

import pandas as pd
df = pd.DataFrame()
df['Date'] = ['6/24/2019','6/14/2019','2019-09-06 00:00:00','6/14/2019','6/14/2019']
df['newDate'] = pd.to_datetime(df['Date'])
print (df)

                  Date    newDate
0            6/24/2019 2019-06-24
1            6/14/2019 2019-06-14
2  2019-09-06 00:00:00 2019-09-06
3            6/14/2019 2019-06-14
4            6/14/2019 2019-06-14

Answer 3

Use to_datetime with both formats and errors='coerce' for NaT if not match and replace missing values by another Series by Series.combine_first or Series.fillna them, last convert to strings by Series.dt.strftime:

s1 = pd.to_datetime(data['Date'], format='%Y-%d-%m %H:%M:%S', errors='coerce')
s2 = pd.to_datetime(data['Date'], format = '%m/%d/%Y', errors='coerce')

#2 possible solutions
data['new'] = s1.fillna(s2).dt.strftime('%m/%d/%Y')
data['new'] = s1.combine_first(s2).dt.strftime('%m/%d/%Y')
print (data)
                  Date         new
0            6/24/2019  06/24/2019
1            6/14/2019  06/14/2019
2  2019-09-06 00:00:00  06/09/2019
3            6/14/2019  06/14/2019
4            6/14/2019  06/14/2019