def common$\_$car$\_$make$()$ :

import xlrd

import pandas as pd

import numpy as $np$

import re

# Filter all warnings. If you would like to see the warnings, please import warnings

warnings. filterwarnings$(\text{'}$ignore$\text{'})$

df $=$ load$\_$ticket$\_$data$()$

# YOUR CODE HERE

import pandas as pd

import random

def load$\_$ticket$\_$data$()$ :

$df=pd.$read$\_$excel$("$random$\_$ticket$\_$data.xlsx$")|$

return $df$

def common$\_$car$\_$make$()$ :

$df=$ load$\_$ticket$\_$data$()$

$[\text{'}$Car Make'$]df[\text{'}$Car Make'$].$ str$.$upper$()$

car$\_$make$\_$counts$=$df $[\text{'}$Car Make'$].$ value$\_$counts$()$

most$\_$common$\_$car$\_$make$=$car$\_$make$\_$counts. index $[0]$

most$\_$common$\_$car$\_$make$=$str$($most$\_$common$\_$car$\_$make$)$

return most$\_$common$\_$car$\_$make

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