[{'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:def estimate_occ(df,room, occupancy_rate):\n'''function that caluclates the estimated number of room occupants\nparameters\n----------\ndf is a dataframe with columns room and occupancy_rate\nroom is a string denoting a column in df that contains INT values representing room IDs\noccupancy_rate is a string denoting a column in df that contains DECIMAL values that represent the estimated room occupancy rate\n'''\nfor i in range(df.shape[0]):\nif df[room][i] == 2 or df[room][i] == 3:\nest = df[occupancy_rate][i] * 90\ndf.set_value(i, 'est_occupants', est)\nelif df[room][i] == 4:\nest = df[occupancy_rate][i] * 220\ndf.set_value(i, 'est_occupants', est)\nelse:\nraise ValueError('Incorrect room number:', df[room][i])"}, {'role': 'assistant', 'content': 'data_preprocessing'}]