[{'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.jointplot(\'GOOG\',\'GOOG\', data = tech_rets, kind=\'scatter\',\ncolor=\'purple\', edgecolor="w", s = 40, alpha = 0.8,\nmarginal_kws=dict(bins=20),\nspace = 0.2, xlim = (-0.06, 0.06), ylim = (-0.06, 0.06))\nfig = plt.gcf()\nfig = plotly.tools.mpl_to_plotly(fig)\nfig[\'layout\'].update(# control x and y axes of the top marginal histogram\nyaxis2 = dict(nticks = 4, showgrid = False),\nxaxis2 = dict(ticks = "", showticklabels = False, showgrid = True),\nyaxis3 = dict(ticks = "", showticklabels = False),\nxaxis3 = dict(nticks = 5, showgrid = False),\nwidth = 900,\nheight = 450)\nplotly.offline.iplot(fig)'}, {'role': 'assistant', 'content': 'data_exploration'}]