Unknown string format: DD/MM/YYYY - HH:MM:SS

Question

I am trying to convert my Date columns of my DataFrame to datetime[ns] which is in the format "%d/%m%Y - %H:%M:%S". I have tried multiple methods like, pd.to_datetime, datetime.strptime, datetime.strftime, etc. But every time its showing the error:

TypeError: Unrecognized value type: <class 'str'> During handling of the above exception, another exception occurred: . . . . . Unknown string format: DD/MM/YYYY - HH:MM:SS.

        Date                Var1    Var2
0   19/03/2021 - 00:01:00   22.52   0
1   19/03/2021 - 00:16:00   22.93   0
2   19/03/2021 - 00:31:00   22.79   0
3   19/03/2021 - 00:46:00   22.65   0
4   19/03/2021 - 01:01:00   22.34   0

above is the sample of my DataFrame.

Your help will be highly appreciated.

Answer 1

for given specific example...

It is typo, you need /:

df = pd.DataFrame({'Date':['19/03/2021 - 00:01:00', 
                           '19/03/2021 - 00:16:00', '19/03/2021 - 00:31:00', 
                           '19/03/2021 - 00:46:00', '19/03/2021 - 01:01:00']})

df['Date'] = pd.to_datetime(df['Date'], format="%d/%m/%Y - %H:%M:%S")
                                                    ^^^
print (df)
                 Date
0 2021-03-19 00:01:00
1 2021-03-19 00:16:00
2 2021-03-19 00:31:00
3 2021-03-19 00:46:00
4 2021-03-19 01:01:00

---

in general...

Tell the computer exactly what to do by selecting from strftime() and strptime() Format Codes. All components of date and time have to be matched by a directive %... while all other characters have to be exactly as in the input. The computer cannot guess that you meant a . to be a / for example:

s = "10.14.1986"
dt = datetime.strptime(s, "%m/%d/%Y")

will fail with

ValueError: time data '10.14.1986' does not match format '%m/%d/%Y'

because I used the wrong delimiter, / should be .