pandas - adding a new column with values from the existing ones -

what's pandas-appropriate way of achieving this? want create column datetime objects 'year','month' , 'day' columns, came code looks way cumbersome:

mylist=[] row in df_orders.iterrows():  #df_orders dataframe     mylist.append(dt.datetime(row[1][0],row[1][1],row[1][2]))     #-->year, month , day 0th,1st , 2nd columns. myseries=pd.series(mylist,index=df_orders.index) df_orders['mydateformat']=myseries 

thanks lot help.

try this:

in [1]: df = pd.dataframe(dict(yyyy=[2000, 2000, 2000, 2000],                                 mm=[1, 2, 3, 4], day=[1, 1, 1, 1])) 

convert integer:

in [2]: df['date'] = df['yyyy'] * 10000 + df['mm'] * 100 + df['day'] 

convert string, datetime (as pd.to_datetime interpret integer differently):

in [3]: df['date'] = pd.to_datetime(df['date'].apply(str))  in [4]: df out[4]:     day  mm  yyyy                date 0    1   1  2000 2000-01-01 00:00:00 1    1   2  2000 2000-02-01 00:00:00 2    1   3  2000 2000-03-01 00:00:00 3    1   4  2000 2000-04-01 00:00:00