pandas df elements from list into column-CodePudding

I have this DF:

Elemento_lista	DISPLAYNAME	Rdo_Encontrado
0	90S VALASION	[('90S VALASION', 100, 0), ('90S VALASION', 100, 1), ('90S VALASION', 100, 2), ('90S VALASION', 100, 3)]
1	ADIZERO RC 2 W	[('ADIZERO RC 2 W', 100, 11), ('ADIZERO RC 2 W', 100, 12), ('ADIZERO RC 2 W', 100, 13), ('ADIZERO RC 2 W', 100, 14)]
2	ASWEERUN	[('ASWEERUN', 100, 16), ('ASWEERUN', 100, 17), ('90S VALASION', 34, 0), ('90S VALASION', 34, 1)]

As it can bee seen, Rdo_Encontrado Column´s value is a List. I need a new row, for each element, and 3 new columns, with values from each list element. The Output should look like this:

Elemento_lista	DISPLAYNAME	Coincidencia	Score	idx
0	90S VALASION	90S VALASION	100	0
0	90S VALASION	90S VALASION	100	1
0	90S VALASION	90S VALASION	100	2
0	90S VALASION	90S VALASION	100	3
1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	11
1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	12
1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	13
1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	14
2	ASWEERUN	ASWEERUN	100	16
2	ASWEERUN	ASWEERUN	100	17
2	ASWEERUN	ASWEERUN	34	0
2	ASWEERUN	ASWEERUN	34	1

Is it possible to do something like this?. I couldn´t find a way...

CodePudding user response：

Try:

# make sure you don't have strings in Rdo_Encontrado column:

from ast import literal_eval
df["Rdo_Encontrado"] = df["Rdo_Encontrado"].apply(literal_eval)



df = df.explode("Rdo_Encontrado")
df[["Coincidencia", "Score", "idx"]] = df.pop("Rdo_Encontrado").apply(pd.Series)
print(df.to_markdown())

Prints:

	Elemento_lista	DISPLAYNAME	Coincidencia	Score	idx
0	0	90S VALASION	90S VALASION	100	0
0	0	90S VALASION	90S VALASION	100	1
0	0	90S VALASION	90S VALASION	100	2
0	0	90S VALASION	90S VALASION	100	3
1	1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	11
1	1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	12
1	1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	13
1	1	ADIZERO RC 2 W	ADIZERO RC 2 W	100	14
2	2	ASWEERUN	ASWEERUN	100	16
2	2	ASWEERUN	ASWEERUN	100	17
2	2	ASWEERUN	90S VALASION	34	0
2	2	ASWEERUN	90S VALASION	34	1

EDIT: Added ast.literal_eval