[{'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:# age<br><br># assign all age values > 100 to NaN, these NaN values will be replaced with real ages below<br>airbnb_df["age"][airbnb_df["age"] > 100] = np.NaN<br>test_df["age"][test_df["age"] > 100]     = np.NaN<br><br># get average, std, and number of NaN values in airbnb_df<br>average_age_airbnb   = airbnb_df["age"].mean()<br>std_age_airbnb       = airbnb_df["age"].std()<br>count_nan_age_airbnb = airbnb_df["age"].isnull().sum()<br><br># get average, std, and number of NaN values in test_df<br>average_age_test   = test_df["age"].mean()<br>std_age_test       = test_df["age"].std()<br>count_nan_age_test = test_df["age"].isnull().sum()<br><br># generate random numbers between (mean - std) & (mean + std)<br>rand_1 = np.random.randint(average_age_airbnb - std_age_airbnb, average_age_airbnb + std_age_airbnb, size = count_nan_age_airbnb)<br>rand_2 = np.random.randint(average_age_test - std_age_test, average_age_test + std_age_test, size = count_nan_age_test)<br><br># fill NaN values in Age column with random values generated<br>airbnb_df["age"][np.isnan(airbnb_df["age"])] = rand_1<br>test_df["age"][np.isnan(test_df["age"])]     = rand_2<br><br># convert type to integer<br>airbnb_df[\'age\'] = airbnb_df[\'age\'].astype(int)<br>test_df[\'age\']   = test_df[\'age\'].astype(int)'}, {'role': 'assistant', 'content': "['data_preprocessing']"}]