[{'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:fig, ax = plt.subplots(1)\nylow, yhigh = ax.set_ylim([0.000001,0.001])\nax.set_yscale("log", nonposy=\'clip\')\nfor id_index in range(33):\nerrors=dat.error_set.where(dat.error_set[\'loc_id\'] == dat.site_info[\'ID\'][id_index]).dropna()[GLE1_begin:GLE1_end]\nplt.plot(errors.index, errors.rate)\nax.fill_betweenx([ylow,yhigh], GLE1[0],GLE1[1], facecolor=\'yellow\', alpha=0.5, label=\'GLE 1\')\nax.set_xlabel(\'Time\')\nax.set_ylabel(\'Error Rate (errors/Gb)\')\nax.set_title(\'{0} {1}\'.format(\'Error Rate\',\'for GLE on 2012-05-17\'))\nGLE_label = mpatches.Patch(color=\'yellow\', label=\'GLE 1\')\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/GLE1_Merged_UnCorrected\',dat.site_info[\'Site\'][id_index],dat.site_info[\'ID\'][id_index],\'.png\'), dpi=200)'}, {'role': 'assistant', 'content': "['data_exploration']"}]