[{'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: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']"}]