[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:word_dict = {}\nip_dict = {}\nauthor_dict = {}\nwebsite_dict = {}\nemail_dict = {}\nhour_dict = {}\ntime_dict = {}\nnum_mistakes_dict = {}\nerror_dict = {}\nwith codecs.open(\'data/spam_data.csv\',\'r\',encoding="utf-8") as spam_data:\nreader = csv.DictReader(spam_data)\nfor row in reader:\ncomment = row[\'Comment\']\nfor word in comment.split():\nword = re.sub("[\\?\\.,\\“!\\"\\”\\(\\)]","",word)\nif word in word_dict:\nword_dict[word] += 1\nelse:\nword_dict[word] = 1\nip = row[\'IP Address\']\nif ip in ip_dict:\nip_dict[ip] += 1\nelse:\nip_dict[ip] = 1\nauthor = row[\'Author\']\nif author in author_dict:\nauthor_dict[author] += 1\nelse:\nauthor_dict[author] = 1\nwebsite = row[\'Website\']\nif website in website_dict:\nwebsite_dict[website] += 1\nelse:\nwebsite_dict[website] = 1\nemail = row[\'Email\']\nif email in email_dict:\nemail_dict[email] += 1\nelse:\nemail_dict[email] = 1\nhour = re.sub(":[\\d]{2}","",row[\'Submit Time\'])\nhour_number = re.match("[\\d]+",hour).group(0)\nif "pm" in hour:\nhour = str((int(hour_number)+12)%24)+":00"\nelse:\nhour = str((int(hour_number))%24)+":00"\nif len(hour) < 5:\nhour = "0"+hour\nif hour in hour_dict:\nhour_dict[hour] += 1\nelse:\nhour_dict[hour] = 1\ntime = re.match("([\\d]+):([\\d]{2})",row[\'Submit Time\'])\ntime_string = ""\nif "pm" in row[\'Submit Time\']:\ntime_string = str((int(time.groups()[0])+12)%24)+":"+str(time.groups()[1])\nelse:\ntime_string = str(int(time.groups()[0]))+":"+str(time.groups()[1])\ntime_check = re.match("([\\d]+):([\\d]{2})",time_string)\nif len(time_check.groups()[0]) < 2:\ntime_string = "0"+time_string\nif time_string in time_dict:\ntime_dict[time_string] += 1\nelse:\ntime_dict[time_string] = 1\nparse_tree = xml.etree.ElementTree.fromstring(row[\'Grammar Check\'])\nnum_mistakes_dict[row[\'Comment Number\']] = [len(parse_tree),row[\'Comment\']]\nerror_dict[row[\'Comment Number\']] = parse_tree'}, {'role': 'assistant', 'content': 'data_preprocessing'}]