import pandas as pd


files_list = ["A", "B", "C", "D"]
files_cont = [
    ["A1"],
    ["A2", "B1"],
    ["A3", "B3", "C3", "C3"],
    [],
]

df3 = pd.DataFrame({"contents": list(map(sorted, map(set, files_cont)))}, index=files_list)
print(df3)

       contents
A          [A1]
B      [A2, B1]
C  [A3, B3, C3]
D            []

import pandas as pd


files_list = ["A", "B", "C", "D"]
files_cont = [
    ["A1"],
    ["A2", "B1"],
    ["A3", "B3", "C3", "C3"],
    [],
]

df3 = pd.DataFrame({"contents": list(map(sorted, map(set, files_cont)))}, index=files_list)
print(df3)

       contents
A          [A1]
B      [A2, B1]
C  [A3, B3, C3]
D            []

We create a new pd.DataFrame using a dict so that the key is used for the column name (I used "contents" but choose whatever you feel like) and providing the index keyword argument to specify the rows.

As the question removed duplicates in the list, each content list is passed first to the set function to eliminate duplicated elements, then to the sorted function to get back a list with sorted elements. If you dont need that just use {"contents": files_cont} instead.