[{'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:#basic features\ntrain_df["price_t"] =train_df["price"]/train_df["bedrooms"]\ntest_df["price_t"] = test_df["price"]/test_df["bedrooms"] \ntrain_df["room_sum"] = train_df["bedrooms"]+train_df["bathrooms"] \ntest_df["room_sum"] = test_df["bedrooms"]+test_df["bathrooms"] \n\n# count of photos #\ntrain_df["num_photos"] = train_df["photos"].apply(len)\ntest_df["num_photos"] = test_df["photos"].apply(len)\n\n# count of "features" #\ntrain_df["num_features"] = train_df["features"].apply(len)\ntest_df["num_features"] = test_df["features"].apply(len)\n\n# count of words present in description column #\ntrain_df["num_description_words"] = train_df["description"].apply(lambda x: len(x.split(" ")))\ntest_df["num_description_words"] = test_df["description"].apply(lambda x: len(x.split(" ")))\n\n\nfeatures_to_use=["bathrooms", "bedrooms", "latitude", "longitude", "price","price_t","num_photos", "num_features", "num_description_words","listing_id"]'}, {'role': 'assistant', 'content': "['data_preprocessing']"}]