[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:df = pd.read_csv(\'cleantable-mb.csv\')\ndf = df[df.SchoolYear<2010]\ndf = df.fillna(0.0)\ndf = df.drop([\'Y\',\'Y2\',\'LongTract\',\'Zip\',\'NextYearCount\',\'TotalCountByTractGrade\'],axis=1) #exclude some columns\ntest_df = df[df.SchoolYear>2008] #Test set 2008, 2009\ntrain_df = df[df.SchoolYear<=2008] # Training set from 2001 to 2007\nres = ols(y=train_df[\'Target\'], x=train_df.drop(\'Target\',axis=1))\nnewy=(test_df.drop(\'Target\',axis=1).dot(res.beta.drop(\'intercept\')) + res.beta[\'intercept\'])\nnewy = newy.apply(int)\nresult = pd.DataFrame({"newy": newy,"actual":test_df[\'Target\']})\nresult.sum(axis=0)\nevaluation(result)'}, {'role': 'assistant', 'content': "['load_data', 'data_preprocessing', 'evaluation', 'modelling', 'prediction']"}]