[{'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:def calculate_trend(df, lag_list, column):\n    for lag in lag_list:\n        trend_column_lag = "Trend_" + column + "_" + str(lag)\n        df[trend_column_lag] = (df[column]-df[column].shift(lag, fill_value=-999))/df[column].shift(lag, fill_value=0)\n    return df\n\n\ndef calculate_lag(df, lag_list, column):\n    for lag in lag_list:\n        column_lag = column + "_" + str(lag)\n        df[column_lag] = df[column].shift(lag, fill_value=0)\n    return df\n\n\nts = time.time()\nall_data = calculate_lag(all_data, range(1,7), \'ConfirmedCases\')\nall_data = calculate_lag(all_data, range(1,7), \'Fatalities\')\nall_data = calculate_trend(all_data, range(1,7), \'ConfirmedCases\')\nall_data = calculate_trend(all_data, range(1,7), \'Fatalities\')\nall_data.replace([np.inf, -np.inf], 0, inplace=True)\nall_data.fillna(0, inplace=True)\nprint("Time spent: ", time.time()-ts)\''}, {'role': 'assistant', 'content': "['data_preprocessing']"}]