Remove duplicates in DF and convert into a JSON obj in python

I have a df something like below

Name         Series
=============================
A             A1
B             B1
A             A2
A             A1
B             B2

I need to convert the series to a list which should be assigned to each Name like a dict or json obj as something like below

{
   "A": ["A1", "A2"],
   "B": ["B1", "B2"]
}

So far I have tried using groupby, but it just groups everything a separate dict

test = df.groupby("Series")[["Name"]].apply(lambda x: x)

The above code gives an output as a df like

         Series
Name
A     0   A1
      2   A2
      3   A1
B     1   B1
      4   B2

Any help is much appreciated

Thanks,

>Solution :

First drop_duplicates to ensure having , then groupby.agg as list:

out = df.drop_duplicates().groupby('Name')['Series'].agg(list).to_dict()

Or with unique:

out = df.groupby('Name')['Series'].agg(lambda x: x.unique().tolist()).to_dict()

Output: {'A': ['A1', 'A2'], 'B': ['B1', 'B2']}

If you have other columns, ensure to only keep those of interest:

out = (df[['Name', 'Series']].drop_duplicates()
       .groupby('Name')['Series'].agg(list).to_dict()
      )

sorting the lists:

out = (df.groupby('Name')['Series']
         .agg(lambda x: sorted(x.unique().tolist())).to_dict()
      )

Example:

# input
  Name Series
0    A     Z1
1    B     B1
2    A     A2
3    A     Z1
4    B     B2

# output
{'A': ['A2', 'Z1'], 'B': ['B1', 'B2']}