pandas group several columns by one

Question

Id    1    2    3    4

z1    3    0    2    2 
z1    1    4    4    3
z2    8    1    7    9
z2    0    0    2    3
z2    5    6    7    9
z3    0    5    6    2
z3    4    4    8    2

Here is my data, I want to group every column into lists by Id, result should be this

Id    1      2      3      4

z1   [3,1]  [0,4]  [2,4]  [2,3]
z2 [8,0,5][1,0,6][7,2,7][9,3,9]
z3   [0,4]  [5,4]  [6,8]  [2,2]

So here is the thing I could do every column separately but I've done that and now I need to optimize this, is there any way for this to be done once for every column?? If not, maybe there is a way that works faster than pandas.groupby??

Answer 1

First I think working with list s in pandas is not good idea .

But if really need it, it is possible by DataFrameGroupBy.agg with list :

df = df.groupby('Id').agg(list)
print (df)
            1          2          3          4
Id                                            
z1     [3, 1]     [0, 4]     [2, 4]     [2, 3]
z2  [8, 0, 5]  [1, 0, 6]  [7, 2, 7]  [9, 3, 9]
z3     [0, 4]     [5, 4]     [6, 8]     [2, 2]