[{'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, ax = plt.subplots(1)\nylow, yhigh = ax.set_ylim([0.000008,0.000035])\nax.set_yscale("log", nonposy=\'clip\')\nfor id_index in [30,31,32]:\nerrors=dat.error_set.where(dat.error_set[\'loc_id\'] == dat.site_info[\'ID\'][id_index]).dropna()[GLE2_begin:GLE2_end]\nplt.plot(errors.index, errors.rate, alpha=0.7)\nplt.gca().set_prop_cycle(None)\nfor id_index in [30,31,32]:\nerrors=dat.error_set.where(dat.error_set[\'loc_id\'] == dat.site_info[\'ID\'][id_index]).dropna().resample(\n\'1h\').median()[GLE2_begin:GLE2_end]\nplt.plot(errors.index, errors.rate, lw=2)\nax.fill_betweenx([ylow,yhigh], GLE2[0],GLE2[1], facecolor=\'orange\', alpha=0.3, label=\'GLE 2\')\nax.set_xlabel(\'Time\')\nax.set_ylabel(\'Error Rate (errors/Gb)\')\nax.set_title(\'{0} {1}\'.format(\'Error Rate\',\'for GLE on 2014-01-06\'))\nGLE_label = mpatches.Patch(color=\'orange\', label=\'GLE 2\')\nplt.legend(handles=[GLE_label], loc=\'upper right\')\nfig.autofmt_xdate()\nplt.tight_layout()\nplt.savefig(\'{0}{1}{2}{3}\'.format(\'/Users/mskirk/Desktop/GooglePlots/GLE2_Merged_Uncorrected\',dat.site_info[\'Site\'][id_index],dat.site_info[\'ID\'][id_index],\'.png\'), dpi=200)'}, {'role': 'assistant', 'content': 'data_exploration'}]