[{'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:df['est_occupants_newcat'] = None\ndf['prediction_max_newcat'] = None\nfor i in range(df.shape[0]):\nif df['occupancy'][i] == 0.0:\ndf.set_value(i, 'est_occupants_newcat', 'empty')\nelif df['occupancy'][i] == 0.25 or df['occupancy'][i] == 0.5:\ndf.set_value(i, 'est_occupants_newcat', 'half')\nelif df['occupancy'][i] == 0.75 or df['occupancy'][i] == 1.0:\ndf.set_value(i, 'est_occupants_newcat', 'full')\nelse:\nraise ValueError('wrong occupancy:', df['occupancy'][i])\nif df['cat_predict'][i] == 0.0:\ndf.set_value(i, 'prediction_max_newcat', 'empty')\nelif df['cat_predict'][i] == 0.25 or df['cat_predict'][i] == 0.5:\ndf.set_value(i, 'prediction_max_newcat', 'half')\nelif df['cat_predict'][i] == 0.75 or df['cat_predict'][i] == 1.0:\ndf.set_value(i, 'prediction_max_newcat', 'full')\nelse:\nraise ValueError('wrong occupancy:', df['cat_predict'][i])"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]