Turn mixed string into datetime object in Pandas

Question

I have a date column that has the following format:

date
10jan2018
12feb2018
14mar2018

And so on. I guess the best approach is to turn the middle string into a number, and then apply todatetime() so I created a dictionary like this:

dict_month={'jan':01, 'feb':02,'mar':03,'apr':04,'may':05,'jun':06'
      'jul':07, 'aug':08,'sep':09,'oct':10,'nov':11,'dec':12}

But I'm not sure how to proceed. Maybe I could use a regex, but I'm not sure how to combine regex and dictionary.

Any ideas?

Brad Solomon · Accepted Answer · 2018-11-15 15:43:25Z

3

Specify a format to pd.to_datetime(). %b is the month as locale’s abbreviated name (and is case-insensitive in this direction):

>>> df
        date
0  10jan2018
1  12feb2018
2  14mar2018

>>> pd.to_datetime(df['date'], format='%d%b%Y')
0   2018-01-10
1   2018-02-12
2   2018-03-14
Name: date, dtype: datetime64[ns]

From datetime module: Formatting directives.

answered Nov 15, 2018 at 15:43

Brad Solomon

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