[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:fig, axes = plt.subplots(2, 3,figsize=(17,10) )\npalette = itertools.cycle(sns.color_palette(n_colors=4))\nplt.subplots_adjust(hspace = 0.28)\n#axes[1].df_train_store.groupby(by="StoreType").count().Store.plot(kind=\'bar\')\naxes[0,0].bar(df_store.groupby(by="StoreType").count().Store.index,df_store.groupby(by="StoreType").count().Store,color=[next(palette),next(palette),next(palette),next(palette)])\naxes[0,0].set_title("Number of Stores per Store Type \\\n Fig 1.1")\naxes[0,1].bar(df_train_store.groupby(by="StoreType").sum().Sales.index,df_train_store.groupby(by="StoreType").sum().Sales/1e9,color=[next(palette),next(palette),next(palette),next(palette)])\naxes[0,1].set_title("Total Sales per Store Type (in Billions) \\\n Fig 1.2")\naxes[0,2].bar(df_train_store.groupby(by="StoreType").sum().Customers.index,df_train_store.groupby(by="StoreType").sum().Customers/1e6,color=[next(palette),next(palette),next(palette),next(palette)])\naxes[0,2].set_title("Total Number of Customers per Store Type (in Millions) \\\n Fig 1.3")\naxes[1,0].bar(df_train_store.groupby(by="StoreType").sum().Customers.index,df_train_store.groupby(by="StoreType").Sales.mean(),color=[next(palette),next(palette),next(palette),next(palette)])\naxes[1,0].set_title("Average Sales per Store Type \\\n Fig 1.4")\naxes[1,1].bar(df_train_store.groupby(by="StoreType").sum().Customers.index,df_train_store.groupby(by="StoreType").Customers.mean(),color=[next(palette),next(palette),next(palette),next(palette)])\naxes[1,1].set_title("Average Number of Customers per Store Type \\\n Fig 1.5")\naxes[1,2].bar(df_train_store.groupby(by="StoreType").sum().Sales.index,df_train_store.groupby(by="StoreType").SalesperCustomer.mean(),color=[next(palette),next(palette),next(palette),next(palette)])\naxes[1,2].set_title("Average Spending per Customer in each Store Type \\\n Fig 1.6")\nplt.show()\''}, {'role': 'assistant', 'content': 'result_visualization'}]