python - Improve performance of Datetime operation in pandas -

i have big data set need date operation, , taking long, wondering if there other way boost speed. data frame looks following:

date, month 2017-01-01, 0 2017-01-01, 1 2017-01-01, 2 

i need create column adds month column date column, following:

date, month, newdate 2017-01-01, 0, 2017-01-01 2017-01-01, 1, 2017-02-01 2017-01-01, 2, 2017-03-01 

my current method using apply function , relativedelta method like:

def newdatecalc(self, row): return row[0] + relativedelta(months = row[1]) 

df['newdate'] = df[['date', 'month']].apply(lambda row: newdatecalc(row), axis = 1)

thank in advance,

here vectorized attempt:

df['newdate'] = (df.date.values.astype('m8[m]') +                   df.month.values * np.timedelta64(1, 'm')).astype('m8[d]') 

result:

in [106]: df out[106]:         date  month    newdate 0 2017-01-01      0 2017-01-01 1 2017-01-01      1 2017-02-01 2 2017-01-01      2 2017-03-01