with open('tab_id_HomeAwayScores_Over_Under_3_5_AWAY3.csv', 'r') as f:
  reader = csv.reader(f)
  your_list_12 = list(reader)
with open('tab_id_Match_Result.csv', 'r') as f:
  reader = csv.reader(f)
  your_list_13 = list(reader)

print("***********************************************************************************************************************************************************************************************************************************")
df = pd.DataFrame({ #'ID'   : your_list[0][0],
                    #'WK'   : your_list[0][1],
                    'H' : your_list_13[0][2:12],
                    'D__' : your_list_13[0][12:22],
                    'A' : your_list_13[0][22:32],
                    'GG__' : your_list[0][2:12],
                    'NG__' : your_list[0][12:22],
                    'OV15' : your_list_0[0][2:12],
                    'UN15' : your_list_0[0][12:22],
                    'Ov25' : your_list_2[0][2:12],
                    'UN25' : your_list_2[0][12:22],
                    'OV35' : your_list_3[0][2:12],
                    'UN35' : your_list_3[0][12:22],
                    'OV45' : your_list_4[0][2:12],
                    'UN45' : your_list_3[0][12:22],
                    'H05'  : your_list_5[0][2:12],
                    'hu5'  : your_list_5[0][12:22],
                    'A05'  : your_list_6[0][2:12],
                    'au5'  : your_list_6[0][12:22],
                    'H15'  : your_list_7[0][2:12],
                    'h15'  : your_list_7[0][12:22],
                    'A15'  : your_list_8[0][2:12],
                    'a15'  : your_list_8[0][2:12],
                    'H25'  : your_list_10[0][2:12],
                    'h25'  : your_list_10[0][12:22],
                    'A25'  : your_list_9[0][2:12],
                    'a25'  : your_list_9[0][12:22],
                    'H35'  : your_list_11[0][2:12],
                    'h35'  : your_list_11[0][12:22],
                    'A35'  : your_list_12[0][2:12],
                    'a35'  : your_list_12[0][12:22]
                    })