[{'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:sns.set_style("whitegrid")\nfig, ax = plt.subplots()\nsns.despine()\nsns.distplot(AAPL[\'Daily Return\'].dropna(), color = "darkcyan", hist_kws = dict(alpha=0.7), ax=ax)\nplotly_fig = plotly.tools.mpl_to_plotly(fig)\nplotly_fig[\'data\'][1][\'marker\'][\'line\'][\'color\'] = \'white\'\nplotly_fig[\'data\'][1][\'marker\'][\'line\'][\'width\'] = 1\nplotly_fig[\'layout\'].update(title = "AAPL Daily Return Distribution",\npaper_bgcolor = \'white\',\nxaxis = dict(showgrid=False),\nwidth = 900,\nheight = 450)\nplotly.offline.iplot(plotly_fig)'}, {'role': 'assistant', 'content': 'data_exploration'}]