[{'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:from scipy import stats\nall_males=np.array([0., allmales['all']['Median income'][1],\nallmales['white']['Median income'][1],\nallmales['black']['Median income'][1],\nallmales['hispanic']['Median income'][1],\nallmales['asian']['Median income'][1]])\nall_females=np.array([0.] + [allfemales[k]['Median income'][1] \\\nfor k in ['all', 'white', 'black',\n'hispanic','asian']])\ncor = stats.spearmanr(all_males, all_females)\nbeta1 = cor[0] * all_females.std() / all_males.std()\nbeta0 = all_females.mean() - beta1 * all_males.mean()\nbeta0, beta1"}, {'role': 'assistant', 'content': 'modelling'}]