[{'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:import numpy as np\nfrom mpl_toolkits.mplot3d import Axes3D\nimport matplotlib.pyplot as plt\nimport random\ndef fun(x, y):\nreturn x**2 + y\nfig = plt.figure()\nax = fig.add_subplot(111, projection='3d')\nx = y = np.arange(-3.0, 3.0, 0.05)\nX, Y = np.meshgrid(x, y)\nzs = np.array([fun(x,y) for x,y in zip(np.ravel(X), np.ravel(Y))])\nZ = zs.reshape(X.shape)\nax.plot_surface(X, Y, Z)\nax.set_xlabel('X Label')\nax.set_ylabel('Y Label')\nax.set_zlabel('Z Label')\nplt.show()"}, {'role': 'assistant', 'content': 'data_exploration'}]