time data does not match format

I get the following error:

time data '07/28/2014 18:54:55.099000' does not match format '%d/%m/%Y %H:%M:%S.%f'

But I cannot see what parameter is wrong in %d/%m/%Y %H:%M:%S.%f ?

This is the code I use.

from datetime import datetime
time_value = datetime.strptime(csv_line[0] + '000', '%d/%m/%Y %H:%M:%S.%f')

I have added and removed the 000 but I get the same error.

Answers


You have the month and day swapped:

'%m/%d/%Y %H:%M:%S.%f'

28 will never fit in the range for the %m month parameter otherwise.

With %m and %d in the correct order parsing works:

>>> from datetime import datetime
>>> datetime.strptime('07/28/2014 18:54:55.099000', '%m/%d/%Y %H:%M:%S.%f')
datetime.datetime(2014, 7, 28, 18, 54, 55, 99000)

You don't need to add '000'; %f can parse shorter numbers correctly:

>>> datetime.strptime('07/28/2014 18:54:55.099', '%m/%d/%Y %H:%M:%S.%f')
datetime.datetime(2014, 7, 28, 18, 54, 55, 99000)

While the above answer is 100% helpful and correct, I'd like to add the following since only a combination of the above answer and reading through the pandas doc helped me:

2-digit / 4-digit year

It is noteworthy, that in order to parse through a 2-digit year, e.g. '90' rather than '1990', a %y is required instead of a %Y.

Infer the datetime automatically

If parsing with a pre-defined format still doesn't work for you, try using the flag infer_datetime_format=True, for example:

yields_df['Date'] = pd.to_datetime(yields_df['Date'], infer_datetime_format=True)

Be advised that this solution is slower than using a pre-defined format.


To compare date time, you can try this. Datetime format can be changed

from datetime import datetime

>>> a = datetime.strptime("10/12/2013", "%m/%d/%Y")
>>> b = datetime.strptime("10/15/2013", "%m/%d/%Y")
>>> a>b
False

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