[{'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:def trim_graph(G, keep=0.25):\n"""Remove nodes that have low betweenness centrality."""\nGt = G.copy()\nrankings = nx.betweenness_centrality(Gt)\nmeans = [(v / len(rankings)) for x, v in rankings.items()]\nind, vals, _ = plt.hist(means, bins = 20, alpha=0.5)\ndef find_index(ind, keep):\ndiscard = np.floor(sum(ind) * (1 - keep))\nreturn np.cumsum(ind) > discard\nthreshold = vals[1:][find_index(ind, 0.25)][0]\nplt.title(\'Histogram of mean betweenness centralities\')\nplt.show()\nfor i, node in enumerate(Gt.nodes()):\nif (rankings[node] / len(rankings)) < threshold:\nGt.remove_node(node)\nreturn Gt, ind, vals'}, {'role': 'assistant', 'content': 'data_exploration'}]