[{'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:gender_age_pclass_group = titanic_safe.groupby([\'Pclass\', assign_age_group, \'Sex\'])[\'Survived\']\nprint(survival_rate_and_total(gender_age_pclass_group))\ntitanic_safe = titanic_safe.rename(columns={\'sex_age_pair\':\'Sex and Age\'})\ntitanic_safe.loc[:, "Passenger Class"] = titanic_safe[\'Pclass\'].map({1:\'First Class\', 2:\'Second Class\', 3:\'Third Class\'})\nt = titanic_safe.groupby([\'Passenger Class\', \'Sex and Age\'], as_index = False)[\'Survived\'].mean()\np = sns.factorplot(data = t, x = \'Sex and Age\', y = \'Survived\', col = \'Passenger Class\', kind = \'bar\')\nsilent = (p.set_axis_labels(\'\', \'Passenger Count\').set_titles(\'{col_name}\'))'}, {'role': 'assistant', 'content': 'data_exploration'}]