Thanks Everyone. Sorry that I’m not clear. I just want to explore PANDAS more. I know this isn’t going to be useful in any of the real world situations but i’m curious. Below is the way I’m able to achieve what I was looking for. Please let me know if there are any other efficient ways of achieving the same.
a= df['A'].dropna().unique()
b= df['B'].dropna().unique()
c= df['C'].dropna().unique()
df_abc = pd.DataFrame({'A' : dict(zip(range(len(a)),a)),
'B': dict(zip(range(len(b)),b)),
'C' :dict(zip(range(len(c)),c))
})
df_abc
A B C
0 one two three
1 NaN NaN Four
solved Create a Dataframe with lists of different sizes [closed]