[{'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:skew_norm_dist = np.random.gamma(4, 2, size=200)\ngridvals = np.arange(0.01, 2, 0.01)\nr_vals = np.array([probplot(box_cox_transform(skew_norm_dist, gridvals[i]))[1][2]\nfor i in range(len(gridvals))])\nbest_val = gridvals[np.argmax(r_vals)]\nf, axes = plt.subplots(1, 3, figsize=(10,5))\naxes[0].set_title("Original Dist")\naxes[1].set_title("Optimal Transform")\naxes[2].set_title("L = {} Prob Plot".format(best_val))\nq0 = axes[0].hist(skew_norm_dist)\nq1 = axes[1].hist(box_cox_transform(skew_norm_dist, best_val))\nq2 = axes[2].scatter(*probplot(box_cox_transform(skew_norm_dist, best_val))[0])'}, {'role': 'assistant', 'content': 'data_exploration'}]