[{'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:# 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# convert the created column to datetime object so as to extract more features \ntrain_df["created"] = pd.to_datetime(train_df["created"])\ntest_df["created"] = pd.to_datetime(test_df["created"])\n\n# Let us extract some features like year, month, day, hour from date columns #\ntrain_df["created_year"] = train_df["created"].dt.year\ntest_df["created_year"] = test_df["created"].dt.year\ntrain_df["created_month"] = train_df["created"].dt.month\ntest_df["created_month"] = test_df["created"].dt.month\ntrain_df["created_day"] = train_df["created"].dt.day\ntest_df["created_day"] = test_df["created"].dt.day\ntrain_df["created_hour"] = train_df["created"].dt.hour\ntest_df["created_hour"] = test_df["created"].dt.hour\n\n# adding all these new features to use list #\nfeatures_to_use.extend(["num_photos", "num_features", "num_description_words","created_year", "created_month", "created_day", "listing_id", "created_hour"])'}, {'role': 'assistant', 'content': 'data_preprocessing'}]