How to make a dataframe with one key to multiple list values to a dictionary in python?

Question

I have a dataframe like this

ID    A    B    
1     3    5
1     4    2
1     0    4
2     2    1
2     4    5
2     9    3
3     2    1
3     4    6

I tried code to convert them from other posts in stackoverflow

df.set_index('ID').T.to_dict('list')

But it gives me a return with each ID with only one list value

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

Is it possible to make a dict like this?

{'1': ([3,5],[4,2],[0,4]), '2': ([2,1],[4,5],[9,3]), '3': ([2,1],[4,6])}

Dictionary keys return IDs, every ID combines with a list of tuples and every tuple contains two values.

Answer 1

In [150]: df.groupby('ID')['A','B'].apply(lambda x: x.values.tolist()).to_dict()
Out[150]:
{'1': [[3, 5], [4, 2], [0, 4]],
 '2': [[2, 1], [4, 5], [9, 3]],
 '3': [[2, 1], [4, 6]]}

Answer 2

defaultdict
This is a good approach. It might have a for loop, require an import , and be multiple lines (all the things that discourage upvotes). But it is actually a good solution and very fast.

from collections import defaultdict

d = defaultdict(list)

for i, a, b in df.values.tolist():
    d[i].append([a, b])

dict(d)

{1: [[3, 5], [4, 2], [0, 4]], 2: [[2, 1], [4, 5], [9, 3]], 3: [[2, 1], [4, 6]]}

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Alternative
Getting a tad creative with numpy.ndarray
BTW: please don't actually do this

pd.Series(
    df[['A', 'B']].values[:, None].tolist(),
    df.ID.values
).sum(level=0).to_dict()

{1: [[3, 5], [4, 2], [0, 4]], 2: [[2, 1], [4, 5], [9, 3]], 3: [[2, 1], [4, 6]]}

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