Take multiple lists into dataframe

I think you're almost there, try removing the extra square brackets around the lst's (Also you don't need to specify the column names when you're creating a dataframe from a dict like this):

import pandas as pdlst1 = range(100)lst2 = range(100)lst3 = range(100)percentile_list = pd.DataFrame(    {'lst1Title': lst1,     'lst2Title': lst2,     'lst3Title': lst3    })percentile_list    lst1Title  lst2Title  lst3Title0          0         0         01          1         1         12          2         2         23          3         3         34          4         4         45          5         5         56          6         6         6...

If you need a more performant solution you can use np.column_stack rather than zip as in your first attempt, this has around a 2x speedup on the example here, however comes at bit of a cost of readability in my opinion:

import numpy as nppercentile_list = pd.DataFrame(np.column_stack([lst1, lst2, lst3]),                                columns=['lst1Title', 'lst2Title', 'lst3Title'])

Adding to Aditya Guru's answer here. There is no need of using map. You can do it simply by:

pd.DataFrame(list(zip(lst1, lst2, lst3)))

This will set the column's names as 0,1,2. To set your own column names, you can pass the keyword argument columns to the method above.

pd.DataFrame(list(zip(lst1, lst2, lst3)),              columns=['lst1_title','lst2_title', 'lst3_title'])

Adding one more scalable solution.

lists = [lst1, lst2, lst3, lst4]df = pd.concat([pd.Series(x) for x in lists], axis=1)