[{'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:bikes = pd.read_csv('../data/2016-Q1-Trips-History-Data.csv')\nbikes['start'] = pd.to_datetime(bikes['Start date'], infer_datetime_format=True)\nbikes['end'] = pd.to_datetime(bikes['End date'], infer_datetime_format=True)\nbikes['datetime_hour'] = bikes.start.dt.floor(freq='h')\nbikes['hour'] = bikes.start.dt.hour\nbikes['day_of_week'] = bikes.start.dt.dayofweek\nbikes['member_cat'] = bikes['Member Type'].map({'Registered':0, 'Casual':1})\nbikes_simp = bikes.drop(['Start date', 'End date', 'Start station',\n'End station', 'Bike number', 'start', 'end', 'datetime_hour', 'Member Type'], axis=1)\nbikes_simp.dtypes"}, {'role': 'assistant', 'content': 'load_data'}]