I have below format of dataframe
student marks
a [12,12,34]
b [34,35]
c [23,45,23]
i want it to convert to like below
student marks_1 marks_2 marks_3
a 12 12 34
b 34 35 Nan
c 23 45 23
how to achieve this ? any help please
Use join new DataFrame created by extracted column marks by pop, convert to lists and use rename for columns by custom lambda function:
f = lambda x: 'marks_{}'.format(x + 1)
df = df.join(pd.DataFrame(df.pop('marks').values.tolist()).rename(columns=f))
print (df)
student marks_1 marks_2 marks_3
0 a 12 12 34.0
1 b 34 35 NaN
2 c 23 45 23.0
Detail:
print (pd.DataFrame(df.pop('marks').values.tolist()))
0 1 2
0 12 12 34.0
1 34 35 NaN
2 23 45 23.0
new_df = pd.DataFrame(df['marks'].tolist()). The pop call just deletes the old column after you use it, and I think you can skip the .values step. Thanks for this answer!Try
dfr = pd.concat([df.student, df.marks.apply(lambda el: pd.Series(
el, index=['marks_{}'.format(i + 1) for i in range(len(el))]))], axis=1)
The code above create an index from each element in marks then concatenate the result with the student column,
The output:
dfr
student marks 1 marks 2 marks 3
0 a 12.0 12.0 34.0
1 b 34.0 35.0 NaN
2 c 23.0 45.0 23.0
