def timechecker(pickuptime, firstdeliverytime, SLA):
    
    secondsinaday = 60 * 60 * 24
    pickuptime_obj, firstdeliverytime_obj = time.localtime(pickuptime), time.localtime(firstdeliverytime)
    pickuptime_seconds, firstdeliverytime_seconds, SLA_seconds = time.mktime(pickuptime_obj), time.mktime(firstdeliverytime_obj), SLA * secondsinaday
    publicholiday_mon_day = [ [3,25],[3,30],[3,31] ]

    totalnonworkingdays = 0
    day_in_seconds = pickuptime_seconds
    day = pickuptime_obj
    
    while day_in_seconds < firstdeliverytime_seconds:
        day = time.localtime(day_in_seconds)
        if ([day.tm_mon,day.tm_mday] in publicholiday_mon_day) or (day.tm_wday == 6):
            totalnonworkingdays += 1
        day_in_seconds += secondsinaday

    timetakeninworkingdays_seconds = firstdeliverytime_seconds - ( totalnonworkingdays * secondsinaday ) - pickuptime_seconds
    if (timetakeninworkingdays_seconds) > SLA_seconds:
        return False
    return True


def is_late(pick,first,second,max_time):
    if type(second) != int:
        if timechecker(pick,first,max_time):
            return 1
        else:
            return 0
    elif type(second) == int:
        if timechecker(pick,first,max_time) and timechecker(first,second,3):
            return 1
        else:
            return 0 

df = pd.read_csv(r'C:\Users\Bob\Downloads\result2.csv')
df.columns=['orderid','pick','fiirst','second','buyeraddress','selleraddress','max_time']
df['is_late'] = df.apply(lambda x: is_late(x.pick, x.fiirst, x.second, x.max_time), axis=1)
df = df.drop(['pick', 'fiirst','second','buyeraddress','selleraddress','max_time'], axis=1)
df.to_csv(r'C:\Users\Bob\Downloads\filename.csv', index = False)