["python","pandas","datetime","indexing","type-conversion"]
How to convert string to datetime format in pandas?

I have a column I_DATE of type string (object) in a dataframe called train as show below. I_DATE 28-03-2012 2:15:00 PM 28-03-2012 2:17:28 PM 28-03-2012 2:50:50 PM How to convert I_DATE from string to datetime format & specify the format of input string. Also, how to filter rows based on a range of dates in pandas?
Use to_datetime. There is no need to specify the format in this case since the parser is able to figure it out. In [51]: pd.to_datetime(df['I_DATE']) Out[51]: 0 2012-03-28 14:15:00 1 2012-03-28 14:17:28 2 2012-03-28 14:50:50 Name: I_DATE, dtype: datetime64[ns] To access the date/day/time component use the dt accessor: In [54]: df['I_DATE'].dt.date Out[54]: 0 2012-03-28 1 2012-03-28 2 2012-03-28 dtype: object In [56]: df['I_DATE'].dt.time Out[56]: 0 14:15:00 1 14:17:28 2 14:50:50 dtype: object You can use strings to filter as an example: In [59]: df = pd.DataFrame({'date':pd.date_range(start = dt.datetime(2015,1,1), end = dt.datetime.now())}) df[(df['date'] > '2015-02-04') & (df['date'] < '2015-02-10')] Out[59]: date 35 2015-02-05 36 2015-02-06 37 2015-02-07 38 2015-02-08 39 2015-02-09