Pandas groupby - set of different values

Question

I have this dataframe

x = pd.DataFrame.from_dict({'cat1':['A', 'A', 'A', 'B', 'B', 'C', 'C', 'C'], 'cat2':['X', 'X', 'Y', 'Y', 'Y', 'Y', 'Z', 'Z']})

  cat1 cat2
0    A    X
1    A    X
2    A    Y
3    B    Y
4    B    Y
5    C    Y
6    C    Z
7    C    Z

I want to group by cat1, and then aggregate cat2 as sets of different values, such as

  cat1 cat2
0    A    (X, Y)
1    B    (Y,)
2    C    (Y, Z)

This is part of a bigger dataframe with more columns, each of which has its own aggregation function, so how do I pass this functionality to the aggregation dictionary?

Answer 1

Use lambda function with set or unique, also convert output to tuples:

x = pd.DataFrame.from_dict({'cat1':['A', 'A', 'A', 'B', 'B', 'C', 'C', 'C'], 
                            'cat2':['X', 'X', 'Y', 'Y', 'Y', 'Y', 'Z', 'Z'],
                             'col':range(8)})
print (x)
  cat1 cat2  col
0    A    X    0
1    A    X    1
2    A    Y    2
3    B    Y    3
4    B    Y    4
5    C    Y    5
6    C    Z    6
7    C    Z    7

a = x.groupby('cat1').agg({'cat2': lambda x: tuple(set(x)), 'col':'sum'})
print (a)
        cat2  col
cat1             
A     (Y, X)    3
B       (Y,)    7
C     (Y, Z)   18

Or:

a = x.groupby('cat1').agg({'cat2': lambda x: tuple(x.unique()), 'col':'sum'})
print (a)
        cat2  col
cat1             
A     (X, Y)    3
B       (Y,)    7
C     (Y, Z)   18

EDIT:

f = lambda x: tuple(x.unique())
f.__name__ = 'my_name'
a = x.groupby('cat1')['cat2'].agg(['min', 'max', 'nunique', f])
print (a)
     min max  nunique my_name
cat1                         
A      X   Y        2  (X, Y)
B      Y   Y        1    (Y,)
C      Y   Z        2  (Y, Z)

If there is only one lambda function or no problem with column name <lambda>:

a = x.groupby('cat1')['cat2'].agg(['min', 'max', 'nunique', lambda x: tuple(x.unique())])
print (a)
     min max  nunique <lambda>
cat1                          
A      X   Y        2   (X, Y)
B      Y   Y        1     (Y,)
C      Y   Z        2   (Y, Z)

Answer 2

Groupby and unique gives you unique values

x.groupby('cat1').cat2.unique()

A    [X, Y]
B       [Y]
C    [Y, Z]

If you want to have the output in tuple, try

x.groupby('cat1').cat2.unique().apply(tuple)

A    (X, Y)
B      (Y,)
C    (Y, Z)