[{'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\nimport matplotlib.pyplot as plt\nfrom pylab import rcParams\nrcParams[\'figure.figsize\'] = 18, 8\nplt.suptitle(\'Fig 1. Sequencing Coverage & Most Frequent Nucleotide by Genome Site\', fontsize=15, fontweight=\'bold\')\nplt.plot (counts_dataframe [\'position\'], counts_dataframe [\'majorbases\'], \'r.\') #(position, coverage, \'r-\')\nplt.plot (counts_dataframe [\'position\'], counts_dataframe [\'coverage\'], \'b-\') #(position, coverage, \'r-\')\nplt.xlabel (\'Genome Position\')\nplt.ylabel (\'Number of Reads\')\nfig_size = rcParams["figure.figsize"]\nplt.legend ([\'The most frequent nucleotide\', \'Sequencing coverage\'], loc = \'upper right\')\naxis_lower_limit = 0\naxis_upper_limit = 330000\nplt.axis ([0, 11000, axis_lower_limit, axis_upper_limit])\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), 10000 + (15000 *(color_counter%3)) , gene.name, rotation=0)\ncolor += 1/len(annots_list)'}, {'role': 'assistant', 'content': 'data_exploration'}]