a for loop to generate multiple data frames in python -

i new python , trying clean code using function generates many data frames desire. want df1, df2, df3, etc. out reading in different lists (one, two, three, etc.). variable "input" same. here code:

thx!

convert list data frame

import numpy np import pandas pd df1 = pd.dataframe(one, columns=[(input.cell(0, 0)).value + 'a',                                  (input.cell(0, 0)).value + 'b',                                  (input.cell(0, 2)).value + 'a',                                  (input.cell(0, 2)).value + 'b',                                  (input.cell(0, 3)).value + 'a',                                  (input.cell(0, 3)).value + 'b',                                  (input.cell(0, 4)).value + 'a',                                  (input.cell(0, 4)).value + 'b',                                  (input.cell(0, 5)).value + 'a',                                  (input.cell(0, 5)).value + 'b',                                  (input.cell(0, 6)).value + 'a',                                  (input.cell(0, 6)).value + 'b',                                  (input.cell(0, 7)).value + 'a',                                  (input.cell(0, 7)).value + 'b',                                  (input.cell(0, 8)).value + 'a',                                  (input.cell(0, 8)).value + 'b',                                  'pos1', 'mut1'])  # replacement of '' nan df1 = df1.replace('', np.nan, regex=true) # calculate differences between individual clones in range(2, 9):     df1[(input.cell(0, i)).value + '_dab'] = diff(df1[(input.cell(0, i))                                                   .value + 'a'],                                                   df1[(input.cell(0, i))                                                   .value + 'b']) 

for in range(number_of_your_desire):     df1[(input.cell(0, i)).value + '_dab'] = diff(df1[(input.cell(0, 2)).value + 'a'], df1[(input.cell(0, i)).value + 'b'])