[{'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:df_sell = df[['selling_price', 'would_purchase', 'count']].groupby(['selling_price', 'would_purchase']).count().unstack()\ndf_sell.index = ['$10-12', '$12-14', '$14-16', '$2-4', '$4-6', '$6-8', '$8-10']\ndf_sell = df_sell.reset_index()\ndf_sell['order'] = [4,5,6,0,1,2,3]\ndf_sell = df_sell.set_index('order').sort_index().set_index('index')\nax = df_sell.plot.bar(title='Student\\'s Meal Valuation', stacked = True,  color=['y','r','g'], rot=0, figsize=(8,6), width=0.9)\nax.legend(['Maybe','No','Yes'], title = 'Purchase at Price')\nax.set_xlabel('Selling Price of a Meal')\nax.set_ylabel('Number of Students')\nax.set_ylim(None, 20)\nax.yaxis.grid(True)\nfig = ax.get_figure()\nfig.savefig('meal_valuation.png')"}, {'role': 'assistant', 'content': 'data_exploration'}]