How to get a dict from a DataFrame that keeps all the values if the values in the column considered as index appear multiple times?

Question

Is there an optimal way to do something like this?

Lets say I have the following DataFrame:

    A   B
0   1   1
1   1   2
2   2   3
3   2   4
4   2   5

I would like to get a dictionary like this:

{1: [1, 2], 2:[3, 4, 5]}

Keep in mind that the lists have different lengths because the value 1 appears two times and the value 2 appears three times. If I try

df.set_index('A').to_dic('list')

Pandas only keeps the last value in B for each value in A, returning the following dict:

{1:[2], 2:[5]

Answer 1

Use DataFrame.groupby with GroupBy.apply with list for Series and then Series.to_dict:

d = df.groupby('A')['B'].apply(list).to_dict()
print (d)
{1: [1, 2], 2: [3, 4, 5]}

Answer 2

You could group by A and the convert the values in B to a list:

result = {key: group['B'].tolist() for key, group in df.groupby('A')}
print(result)

Output

{1: [1, 2], 2: [3, 4, 5]}