Create a parse function for different date formats in Python

Question

I want to create a parse function with lambda able to recognize two different formats

"2014-01-06 15:23:00"

and

"2014-01-06"

The idea is to use this function to create a pandas dataframe but in some of the values the hour is missing

This is my first idea

parse = lambda x: pd.datetime.strptime(x, '%Y-%m-%d %H:%M:%S') if x is True else pd.datetime.strptime(x, '%Y-%m-%d')

it seems that x is True is not correct

Any idea??

As an advise,since you need to handle some exceptions and errors in your function i think lambda is not a correct choice for this task! and so when you use a def all the ties will be open! — Kasravnd
– Kasravnd, Commented Jul 4, 2015 at 14:52

Mike · Accepted Answer · 2015-07-04 14:58:30Z

2

dateutil has a parser that handles multiple formats:

>>> dateutil.parser.parse('2015-07-04')
datetime.datetime(2015, 7, 4, 0, 0)

>>> dateutil.parser.parse('2015-07-04 11:23:00')
datetime.datetime(2015, 7, 4, 11, 23)

>>> dateutil.parser.parse('2015-07-04T11:23:56')
datetime.datetime(2015, 7, 4, 11, 23, 56)

Even non iso formats like this

>>> dateutil.parser.parse('5-6-15')
datetime.datetime(2015, 5, 6, 0, 0)

answered Jul 4, 2015 at 14:58

Mike

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4 Comments

gis20 Over a year ago

Thanks Mike. Yes I know but with dd-mm-yy format does not produce the right ouput result. In your example ('5-6-15') gives datetime.datetime(2015, 5, 6, 0, 0) instead of (2015, 6, 5, 0, 0)

Mike Over a year ago

dd-mm-yy is not typically the way dates are written (at least not in the U.S.) Generally if you put the year at the end its month-day-year.

gis20 Over a year ago

Sure but i am not in the U.S. I am in Europe so my input has dd-mm-yyyy en.wikipedia.org/wiki/Date_format_by_country

Mike Over a year ago

You may have to create a special case then, I don't think the parse function was meant to work with that format.

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