Add Multiple Columns to Pandas Dataframe from Function
If you have a pandas data frame mydf that has, for example, two columns mydate and mytime (both are of type datetime), to add three more columns: hour, weekday, and weeknum, one can write and execute the following code chunk.
def getH(t): #gives the hour
return t.hour
def getW(d): #gives the week number
return d.isocalendar()[1]
def getD(d): #gives the weekday
return d.weekday() # 0 for Monday, 6 for Sunday
mydf["hour"] = mydf.apply(lambda row:getH(row["mytime"]), axis=1)
mydf["weekday"] = mydf.apply(lambda row:getD(row["mydate"]), axis=1)
mydf["weeknum"] = mydf.apply(lambda row:getW(row["mydate"]), axis=1)
Another approach (solution) is:
lambdafunc = lambda x: pd.Series([x['mytime'].hour,
x['mydate'].isocalendar()[1],
x['mydate'].weekday()])
mydf[['hour', 'weekday', 'weeknum']] = mydf.apply(lambdafunc, axis=1)
More details can be found here.
