[{'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:%matplotlib inline\nrcParams[\'figure.figsize\'] = 18, 8\nmoving_average10_proberror = (runningMeanFast (counts_dataframe [\'probability_of_seq_error\'], 10))\nplt.suptitle(\'XXXXXXX\', fontsize=15, fontweight=\'bold\')\nplt.plot (counts_dataframe [\'position\'], moving_average10, \'r-\') #(position, coverage, \'r-\')\nplt.plot (counts_dataframe [\'position\'], 1-moving_average10_proberror, \'k.\')\nplt.xlabel (\'Genome Position\')\nplt.ylabel (\'Probability of Sequencing Error\')\naxis_lower_limit = 0.88\nplt.axis ([0, 11000, axis_lower_limit, 1])\ncolor = 0.0\nfcolor = list (\'bgrcmybgrcmybgrcmybgrcmy\')\ncolor_counter = 0\nfor gene in annots_list:\ncolor_counter +=1\nplt.axvspan(gene.start, gene.end, color = (fcolor [color_counter]), alpha = 0.1) #, label=\'NS5B\')\nplt.text (gene.start + ((gene.end - gene.start)/10), axis_lower_limit + (axis_lower_limit/100) + (((1 - axis_lower_limit) /20) *(color_counter%3)) , gene.name, rotation=0)\ncolor += 1/len(annots_list)\nfig_size = rcParams["figure.figsize"]\nplt.legend ([\'Probability of sequencing error by genome position\'], loc = \'upper right\')\nNone'}, {'role': 'assistant', 'content': 'data_exploration'}]