How to turn column with lists into dataframe?

I have a dataset:

val
[0.5, 0.7,....,0.8]
[0.11, 0.4,....,0.77]
...
[0.99, 0.1,....,0.4]

it is pandas.core.series.Series

there are 1000 rows and 200 values in each list. I want to turn it into dataframe with 200 columns and 1000 rows, but when I do pd.DataFrame(list(df)) it says NumPy.float64 object is not iterable. How to fix it?

>Solution :

You could use a dictionary comprehension:

import pandas as pd
s = pd.Series([[1,2,3],[4,5,6]])  # please provide a reproducible example
pd.DataFrame.from_dict({i:col for i,col in s.iteritems()})

returns

   0  1
0  1  4
1  2  5
2  3  6

You could also use from_records with a transpose:

pd.DataFrame.from_records(s).transpose()