[{'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:labelEncoder = LabelEncoder()\ntrain_dataset[\'Date\'] = pd.to_datetime(train_dataset[\'Date\']).dt.strftime("%m%d").astype(int) \ntrain_dataset[\'Date\'] -= 122 \ntest_dataset[\'Date\'] = pd.to_datetime(test_dataset[\'Date\']).dt.strftime("%m%d").astype(int) \ntest_dataset[\'Date\'] -= 122 \n\ntrain_dataset.Province_State = labelEncoder.fit_transform(train_dataset.Province_State)\ntrain_dataset.Country_Region = labelEncoder.fit_transform(train_dataset.Country_Region)\n\ntest_dataset.Province_State = labelEncoder.fit_transform(test_dataset.Province_State)\ntest_dataset.Country_Region = labelEncoder.fit_transform(test_dataset.Country_Region)\n\n\nprint(\'\\\n\\\n\\\nTrain Dataset After Encoding\')\nprint(train_dataset.head(5))\n      \n\nprint(\'\\\n\\\n\\\nTest Dataset After Encoding\')\nprint(test_dataset.head(5))\n\n\''}, {'role': 'assistant', 'content': "['data_preprocessing']"}]