How to create a dataframe from a nested list of multiple common elements

Question

Say I have any nested list, for example

A = [[120, \'Date1\', 1.03], [120, \'Date2\', 1.04], [120, \'Date3\', 1.02], [240, \'Date1\', 1         


        

Answer 1

You can first convert your list to a dict and then build a DataFrame directly.

d = {}
[d.setdefault(e[0],{}).update({e[1]:e[2]}) for e in A]
df = pd.DataFrame(d)

        120     240     381
Date1   1.03    1.06    NaN
Date2   1.04    0.98    1.03
Date3   1.02    1.04    0.85

Answer 2

Create DataFrame by constructor and then DataFrame.pivot with DataFrame.rename_axis:

df = pd.DataFrame(A).pivot(1,0,2).rename_axis(index=None, columns=None)
print (df)
        120   240   381
Date1  1.03  1.06   NaN
Date2  1.04  0.98  1.03
Date3  1.02  1.04  0.85