find most recent date in pandas dataframe

Question

I have a csv file, that I read into a pandas dataframe. The date and times are listed in a column "DateTime". I want to find the most recent and the least recent date to create an index to create a time series graph. Does pandas have a function that will return the most recent and the least recent date?

Edit:
I already tried using min and max. They give incorrect answers.

>>> f['Start Date']   Trip ID   4576       8/29/2013 14:13   4607       8/29/2013 14:42   4130       8/29/2013 10:16   4251       8/29/2013 11:29   4299       8/29/2013 12:02   4927       8/29/2013 18:54   4500       8/29/2013 13:25   4563       8/29/2013 14:02   4760       8/29/2013 17:01   4258       8/29/2013 11:33   4549       8/29/2013 13:52   4498       8/29/2013 13:23   4965       8/29/2013 19:32   4557       8/29/2013 13:57   4386       8/29/2013 12:31   ...   198757     2/28/2014 20:40   198760     2/28/2014 20:59   198761     2/28/2014 20:59   198763     2/28/2014 21:32   198764     2/28/2014 21:32   198765     2/28/2014 21:34   198766     2/28/2014 21:41   198767     2/28/2014 21:50   198768     2/28/2014 21:54   198770     2/28/2014 22:19   198771     2/28/2014 22:15   198772     2/28/2014 22:38   198773     2/28/2014 22:45   198774     2/28/2014 23:01   198775     2/28/2014 23:20   Name: Start Date, Length: 144015, dtype: object   >>> min(f['Start Date'])   '1/1/2014 0:14'   >>> max(f['Start Date'])   '9/9/2013 9:59'   

Answer 1

First convert your date column in to a datetime column using

>> df['StartDate'] = pd.to_datetime(df['StartDate']) 

You then can find the oldest date and most recent date using

>> least_recent_date = df['StartDate'].min() >> most_recent_date = df['StartDate'].max()