[{'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(3, 1, figsize=(40, 30))\nfor variable, subplot in zip(categorical_features, ax.flatten()):\n    df_2 = df_train[[variable,'revenue']].groupby(variable).revenue.sum().reset_index()\n    df_2.columns = [variable,'total_revenue']\n    sns.barplot(x=variable, y='total_revenue', data=df_2 , ax=subplot)\n    subplot.set_xlabel(variable,fontsize=20)\n    subplot.set_ylabel('Total Revenue',fontsize=20)\n    for label in subplot.get_xticklabels():\n        label.set_rotation(45)\n        label.set_size(20)\n    for label in subplot.get_yticklabels():\n        label.set_size(20)\nfig.tight_layout()"}, {'role': 'assistant', 'content': "['result_visualization']"}]