[{'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:expected_street_types = ["Street", "Avenue", "Boulevard", "Drive", "Court", "Place", "Square", "Lane", "Road",\n"Trail", "Parkway", "Commons"]\n\'\'\'\nReference:  Udacity\n\'\'\'\ndef audit_street_type(street_types, street_name):\nm = street_type_re.search(street_name)\nif m:\nstreet_type = m.group()\nif street_type not in expected_street_types:\nstreet_types[street_type].add(street_name)\ndef print_sorted_dict(d):\nkeys = d.keys()\nkeys = sorted(keys, key=lambda s: s.lower())\nfor k in keys:\nv=d[k]\nprint(\'%s: %d\' % (k, v))\ndef is_street_name(elem):\nreturn (elem.attrib[\'k\'] == \'addr:street\')\ndef audit_streets():\nfor event, elem in xET.iterparse(SMALL_SAMPLE_FILE, events=(\'start\',)):\nif elem.tag == "node" or elem.tag == \'way\':\nfor tag in elem.iter(\'tag\'):\nif is_street_name(tag):\naudit_street_type(street_types, tag.attrib[\'v\'])\nprint(\'Total Ways: \', len(street_types)) #Total Number of Different Types of Streets\npprint.pprint(dict(street_types))#List of Street Types\ndef is_zipcode(elem):\nreturn (elem.attrib[\'k\'] == \'addr:postcode\')\ndef audit_zips():\nzipcodes = {}\ninv_zipcodes = {}\nfor event, elem in xET.iterparse(SAMPLE_FILE, events=(\'start\',)):\nif elem.tag == "node" or elem.tag == "way":\nfor tag in elem.iter("tag"):\nif is_zipcode(tag): #and tag.attrib[\'v\'].startswith(\'98\')\nzipc = tag.attrib[\'v\']\nif zipc not in zipcodes.keys():\nzipcodes[zipc] = 1\nelse:\nzipcodes[zipc] = zipcodes[zipc] + 1\nif not tag.attrib[\'v\'].startswith(\'98\'):\ninv_zipc = tag.attrib[\'v\']\nif inv_zipc not in inv_zipcodes.keys():\ninv_zipcodes[inv_zipc] = 1\nelse:\ninv_zipcodes[inv_zipc] = inv_zipcodes[inv_zipc] + 1\nprint(\'Total Zipcodes: \', len(zipcodes)) #Total Number of Zipcodes\nprint(\'Invalid Zipcodes: \', len(inv_zipcodes)) #Total Number of Invalid Zipcodes\npprint.pprint(dict(inv_zipcodes)) #List of Invalid Zipcodes\naudit_zips()\naudit_streets()'}, {'role': 'assistant', 'content': 'data_exploration'}]