Add column with number of days between dates in DataFrame pandas

I want to subtract dates in 'A' from dates in 'B' and add a new column with the difference.

    df
              A        B
    one 2014-01-01  2014-02-28 
    two 2014-02-03  2014-03-01

I've tried the following, but get an error when I try to include this in a for loop...

    import datetime
    date1=df['A'][0]
    date2=df['B'][0]
    mdate1 = datetime.datetime.strptime(date1, "%Y-%m-%d").date()
    rdate1 = datetime.datetime.strptime(date2, "%Y-%m-%d").date()
    delta =  (mdate1 - rdate1).days
    print delta

What should I do?

Assuming these were datetime columns (if they're not apply to_datetime) you can just subtract them:

    df['A'] = pd.to_datetime(df['A'])
    df['B'] = pd.to_datetime(df['B'])

    In [11]: df.dtypes  # if already datetime64 you don't need to use to_datetime
    Out[11]:
    A    datetime64[ns]
    B    datetime64[ns]
    dtype: object

    In [12]: df['A'] - df['B']
    Out[12]:
    one   -58 days
    two   -26 days
    dtype: timedelta64[ns]

    In [13]: df['C'] = df['A'] - df['B']

    In [14]: df
    Out[14]:
                 A          B        C
    one 2014-01-01 2014-02-28 -58 days
    two 2014-02-03 2014-03-01 -26 days

Note: ensure you're using a new of pandas (e.g. 0.13.1), this may not work in older versions.

From: stackoverflow.com/q/22132525