Converting a dataframe to dictionary with multiple values

Question

I have a dataframe like

Sr.No   ID       A         B          C         D
 1     Tom     Earth    English      BMW
 2     Tom     Mars     Spanish      BMW               


        

Answer 1

You can use groupby with orient of to_dict as list and convert the resultant series to a dictionary.

df.set_index('Sr.No', inplace=True)
df.groupby('ID').apply(lambda x: x.to_dict('list')).reset_index(drop=True).to_dict()

{0: {'C': ['Mercedes', 'Audi'], 'ID': ['John', 'John'], 'A': ['Venus', nan],  
     'B': ['Portugese', 'German'], 'D': ['Blue', 'Red']}, 
 1: {'C': ['Audi'], 'ID': ['Michael'], 'A': ['Mercury'], 'B': ['Hindi'], 'D': ['Yellow']}, 
 2: {'C': ['BMW', 'BMW'], 'ID': ['Tom', 'Tom'], 'A': ['Earth', 'Mars'], 
     'B': ['English', 'Spanish'], 'D': [nan, 'Green']}}

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Inorder to remove ID, you can also do:

df.groupby('ID')['A','B','C','D'].apply(lambda x: x.to_dict('list'))  \
                                 .reset_index(drop=True).to_dict()