I have a df similar to the one below
name series ============================= a a1 b b1 a a2 a a1 b b2
I need to convert the series into a list which should be assigned to each name like dictionary or json obj like below
{ "a": ["a1", "a2"], "b": ["b1", "b2"] }
So far I have tried using groupby but it just groups everything into a single dictionary
test = df.groupby("series")[["name"]].apply(lambda x: x)
The above code gives a df-like output
Series Name A 0 A1 2 A2 3 A1 B 1 B1 4 B2
Any help is greatly appreciated
Thank you
Firstdrop_duplicates
Make sure there is, thengroupby. agg
as a list:
out = df.drop_duplicates().groupby('name')['series'].agg(list).to_dict()
Or dial unique
:
out = df.groupby('name')['series'].agg(lambda x: x.unique().tolist()).to_dict()
Output: {'a': ['a1', 'a2'], 'b': ['b1', 'b2']}
If you have additional columns, make sure to keep only the columns of interest:
out = (df[['name', 'series']].drop_duplicates() .groupby('name')['series'].agg(list).to_dict() )
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']}
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