[{'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:# clean lat, long info, 0s are missing, also set out of china to missing\nevents['longitude'] = events['longitude'].round(0)\nevents['latitude'] = events['latitude'].round(0)\n\n#set out of China to missing along with 0s\nevents['longitude'] = events['longitude'].clip_lower(73.0).replace(73.0, np.NaN) \nevents['longitude'] = events['longitude'].clip_upper(135.0).replace(135.0, np.NaN) \nevents['latitude'] = events['latitude'].clip_lower(15.0).replace(15.0, np.NaN)\nevents['latitude'] = events['latitude'].clip_upper(60.0).replace(60.0, np.NaN)\n\n# lot of missing values - replace them with mode (most common lat, long)\nevents['latitude2'] =events.groupby(['device_id'])['latitude'].transform(lambda x: x.mode()) \nevents['longitude2'] =events.groupby(['device_id'])['longitude'].transform(lambda x: x.mode())"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]