GroupBy results to dictionary of lists

You could groupby on Column1 and then take Column3 to apply(list) and call to_dict?

In [81]: df.groupby('Column1')['Column3'].apply(list).to_dict()Out[81]: {0: [1], 1: [2, 3, 5], 2: [1, 2], 3: [4, 5], 4: [1], 5: [1, 2, 3]}

Or, do

In [433]: {k: list(v) for k, v in df.groupby('Column1')['Column3']}Out[433]: {0: [1], 1: [2, 3, 5], 2: [1, 2], 3: [4, 5], 4: [1], 5: [1, 2, 3]}

python pandas xlrd

According to the docs, the GroupBy.groups:

is a dict whose keys are the computed unique groups and corresponding values being the axis labels belonging to each group.

If you want the values themselves, you can groupby 'Column1' and then call apply and pass the list method to apply to each group.

You can then convert it to a dict as desired:

In [5]:dict(df.groupby('Column1')['Column3'].apply(list))Out[5]:{0: [1], 1: [2, 3, 5], 2: [1, 2], 3: [4, 5], 4: [1], 5: [1, 2, 3]}

(Note: have a look at this SO question for why the numbers are followed by L)

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