[{'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:#ConfirmedCases and Fatalities data Analysis and Visualization for China\nconfirmed_total_date_China = xtrain[xtrain[\'Country_Region\']==\'China\'].groupby([\'Date\']).agg({\'ConfirmedCases\':[\'sum\']})\nfatalities_total_date_China = xtrain[xtrain[\'Country_Region\']==\'China\'].groupby([\'Date\']).agg({\'Fatalities\':[\'sum\']})\ntotal_date_China = confirmed_total_date_China.join(fatalities_total_date_China)\n\nfig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\ntotal_date_China.plot(ax=ax1)\nax1.set_title("China confirmed cases", size=13)\nax1.set_ylabel("Number of cases", size=13)\nax1.set_xlabel("Date", size=13)\nfatalities_total_date_China.plot(ax=ax2, color=\'orange\')\nax2.set_title("China Fatalities cases", size=13)\nax2.set_ylabel("Number of cases", size=13)\nax2.set_xlabel("Date", size=13)\''}, {'role': 'assistant', 'content': "['result_visualization']"}]