How to Convert Pandas Dataframe to Dictionary in Python-CodePudding

I have below dataframe.

**Col1**    **Col2**
ABC           S1
ABC           S2
BCD           S3
FJK           S5
XYZ           S7
XYZ           S8

I need output in the below format.

data = {'ABC': '[S1,S2]', 'BCD': '[S3]', 'FJK': '[S5]', 'XYZ': '[S7,S8]'}

Can anyone please help me how to achieve above output, it will be great !

CodePudding user response：

Like mentioned commnent aggregate list and then convert to dictionary:

d = df.groupby('Col1').Col2.agg(list).to_dict()
print (d)
{'ABC': ['S1', 'S2'], 'BCD': ['S3'], 'FJK': ['S5'], 'XYZ': ['S7', 'S8']}

For strings use f-strings in lambda function:

d = df.groupby('Col1').Col2.agg(lambda x: f"[{','.join(x)}]").to_dict()
print (d)
{'ABC': '[S1,S2]', 'BCD': '[S3]', 'FJK': '[S5]', 'XYZ': '[S7,S8]'}

j = df.groupby('Col1').Col2.agg(list).to_json()
print (j)
{"ABC":["S1","S2"],"BCD":["S3"],"FJK":["S5"],"XYZ":["S7","S8"]}

CodePudding user response：

If you really want a string as value, use aggregation as string:

data = ('[' df.groupby('Col1')['Col2'].agg(','.join) ']').to_dict()

Output:

{'ABC': '[S1,S2]',
 'BCD': '[S3]',
 'FJK': '[S5]',
 'XYZ': '[S7,S8]'}