What is the difference between pandas agg and apply function?

Question

I can\'t figure out the difference between Pandas .aggregate and .apply functions.
Take the following as an example: I load a dataset, do a

Answer 1

The main difference between apply and aggregate is:

apply()- 
    cannot be applied to multiple groups together 
    For apply() - We have to get_group()
    ERROR : -iris.groupby('Species').apply({'Sepal.Length':['min','max'],'Sepal.Width':['mean','min']})# It will throw error
    Work Fine:-iris.groupby('Species').get_group('Setosa').apply({'Sepal.Length':['min','max'],'Sepal.Width':['mean','min']})# It will throw error
        #because functions are applied to one data frame

agg()- 
    can be applied to multiple groups together
    For apply() - We do not have to get_group() 
    iris.groupby('Species').agg({'Sepal.Length':['min','max'],'Sepal.Width':['mean','min']})
    iris.groupby('Species').get_group('versicolor').agg({'Sepal.Length':['min','max'],'Sepal.Width':['mean','min']})