Pandas dataframe to dict on multiple columns and values to list

Question

I have a dataframe

I want to create a dictionary with key as machine no, and id column as list

like:

{1: ['a1', 'a2', 'a3'], 2: ['a4', 'a5'], 3: ['a6']}

Can i use groupby first and then do .to_dict?

there was a conversation about it there : https://stackoverflow.com/questions/18695605/python-pandas-dataframe-to-dictionary — Marine Galantin, Jun 07 '20 at 19:50

score 3 · Accepted Answer · answered Jun 23 '17 at 05:53

3

I believe you need lists ad values of dict - use groupby + apply + to_dict:

d = df.groupby('key')['id'].apply(list).to_dict()
print (d)
{1: ['a1', 'a2', 'a3'], 2: ['a4', 'a5'], 3: ['a6']}

Or if need list with scalars add if/else to apply:

d = df.groupby('key')['id'].apply(lambda x: list(x) if len(x) > 1 else x.iat[0]).to_dict()
print (d)
{1: ['a1', 'a2', 'a3'], 2: ['a4', 'a5'], 3: 'a6'}

answered Jun 23 '17 at 05:53

jezrael

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this is great if we have one column, however, what if we have to get values from multiple columns? I came across a similar situation. I tried using this, but no success. I think `map` would do it, but not sure! If you are willing, I posted a question here: https://stackoverflow.com/questions/46623452/map-two-data-frames-to-create-a-dictionary-with-multiple-values-for-a-key-pand – i.n.n.m Oct 07 '17 at 18:45

score 1 · Answer 2 · answered Jun 23 '17 at 06:01

1

Use a dictionary comprehension around the groupby iterator

{n: v.tolist() for n, v in df.groupby('key').id}

answered Jun 23 '17 at 06:01

piRSquared

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Pandas dataframe to dict on multiple columns and values to list

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