[{'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.optimize import curve_fit\nimport matplotlib.pyplot as plt\n\ndef log_growth(x, a,r,c):\n    return 1.0*c/(1+a * np.exp(-r * x))\n\ndef get_log_fit_params(data):\n    try:\n        popt, pcov = curve_fit(log_growth, data.NumDate, data.ConfirmedCases, method="lm")\n        return popt\n    except RuntimeError:\n        try:\n            popt, pcov = curve_fit(log_growth, data.NumDate, data.ConfirmedCases, method="trf")\n        except RuntimeError:\n            return np.zeros(3)\n\ndf_popt = df_train.groupby("Country").apply(get_log_fit_params)\ndf_opt = df_popt.apply(pd.Series)\ndf_opt.set_axis(["a", "r", "c"], axis=1, inplace=True)\ndf_opt.head()'}, {'role': 'assistant', 'content': 'helper_functions'}]