[{'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:import os\nimport pandas as pd\nimport numpy as np\ndata_folder = os.path.join(os.path.expanduser("~"), "Data")\nroot_folder = "E:/project/pychram/trade_notebook/data-mining"\ndata_folder = os.path.join(root_folder, "Data")\ndata_filename = os.path.join(data_folder, "Ads", "ad.data")\ndef convert_number(x):\ntry:\nreturn float(x)\nexcept ValueError:\nreturn np.nan\nfrom collections import defaultdict\nconverters = defaultdict(convert_number)  #{i: convert_number for i in range(1558)}\nfor i in range(0,1558):\nconverters[i] = convert_number\nconverters[1558] = lambda x: 1 if x.strip() == "ad." else 0\nads = pd.read_csv(data_filename, header=None, converters=converters, low_memory=False)'}, {'role': 'assistant', 'content': 'load_data'}]