[{'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:#np.any(np.isnan(train_users['id']))\n#print(np.all(np.isfinite(col)))\n\n#np.isnan(train_users.any())\n#np.isfinite(train_users.any())\n\n#np.isnan(test_users.any())\n#np.isfinite(test_users.any())\n\n\n\n\n#train_users.head()\n\n\nX_train = train_users_imputed.drop(['signup_app', 'affiliate_provider', 'affiliate_channel', 'levenshtein_distance_from_en', 'month_year_first_active', 'month_year_created', 'year_first_active', 'timestamp_first_active_year', 'country_destination', 'id', 'first_browser', 'age', 'language'], axis=1)\ny_train = train_users_imputed['country_destination']\nX_test = test_users_imputed.drop(['signup_app', 'affiliate_provider', 'affiliate_channel', 'levenshtein_distance_from_en', 'month_year_first_active', 'month_year_created', 'year_first_active', 'timestamp_first_active_year', 'id', 'age', 'first_browser', 'language'], axis = 1)\n"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]