Add Multiple Columns to Pandas Dataframe from Function

Question

I have a pandas data frame mydf that has two columns,and both columns are datetime datatypes: mydate and mytime. I want to add three more

Answer 1

To complement John Galt's answer:

Depending on the task that is performed by lambdafunc, you may experience some speedup by storing the result of apply in a new DataFrame and then joining with the original:

lambdafunc = lambda x: pd.Series([x['mytime'].hour,
                                  x['mydate'].isocalendar()[1],
                                  x['mydate'].weekday()])

newcols = df.apply(lambdafunc, axis=1)
newcols.columns = ['hour', 'weekday', 'weeknum']
newdf = df.join(newcols) 

Even if you do not see a speed improvement, I would recommend using the join. You will be able to avoid the (always annoying) SettingWithCopyWarning that may pop up when assigning directly on the columns:

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead