[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:train2 = pd.read_csv("/kaggle/input/bike-sharing-demand/train.csv", parse_dates=[\'datetime\'])\ntrain2[\'year\'] = train2[\'datetime\'].dt.year\ntrain2[\'month\'] = train2[\'datetime\'].dt.month\ntrain2[\'day\'] = train2[\'datetime\'].dt.day\ntrain2[\'weekday\'] = train2[\'datetime\'].dt.weekday\ntrain2[\'hour\'] = train2[\'datetime\'].dt.hour\n\ntest2 = pd.read_csv(\'/kaggle/input/bike-sharing-demand/test.csv\', parse_dates=[\'datetime\'])\ntest2[\'day\'] = test2[\'datetime\'].dt.day\n\n#  ()   ,       \n# mean   . outlier , median \n#train2.groupby(\'hour\')[\'count\'].mean()\n##### media          .        .\ntrain2.groupby(\'hour\')[\'count\'].median()\n\''}, {'role': 'assistant', 'content': "['data_preprocessing']"}]