[{'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:output_data = pd.DataFrame(columns=wifi_data.columns)  #creating empty output table based on input table\nfor room in wifi_data[\'Room\'].unique():  # for each room\nroom_data = wifi_data[wifi_data[\'Room\'] == room]\nfor date in room_data[\'Date\'].unique():  # for each date\ndate_wifi_data = room_data[room_data[\'Date\'] == date]\nfor index in range(len(hours)-1):  # for each range of hour\ntime_data = date_wifi_data.between_time(hours[index], hours[index+1])\nif time_data["Assoc"].count():\nmax_value = time_data["Assoc"].max()  # choosing the max Assoc from selected data\nmax_time_data = time_data[time_data["Assoc"] == max_value].iloc[0]\noutput_data = output_data.append(max_time_data)'}, {'role': 'assistant', 'content': "['data_preprocessing']"}]