[{'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:#we now do the analysis of Hubei as per week.\nimport warnings\nwarnings.filterwarnings('ignore')\nchina_t = china[china['Province_State'] == 'Hubei']\nchina_t['Date'] = pd.to_datetime(china_t['Date'])\nchina_t.insert(6,'Week',china_t['Date'].dt.week)\nf,axes = plt.subplots(1,2,figsize=(12,5))\nsns.lineplot(x = 'Week',y = 'ConfirmedCases',color='r',data=china_t,ax = axes[0])\nsns.lineplot(x = 'Week',y = 'Fatalities',color='b',data=china_t,ax = axes[1])\n\naxes[0].title.set_text('Confirmed Cases in Hubei per week')\n\naxes[1].title.set_text('Fatalities in Hubei per week')"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]