[{'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:# get original datetime column for submission\ntestdates = testset.datetime\n# create date feature from datetime\ntestset.insert(1, 'date', pd.DataFrame([x[:10] for x in testset.datetime]))\n# create time feature from datetime\ntestset.insert(2, 'time', pd.DataFrame([x[11:] for x in testset.datetime]))\n# convert datetime from string to datetime\ntestset.date = [dt.strptime(x, '%Y-%m-%d').weekday() for x in testset.date]\n# drop datetime column since we created two variables and casual and registered since their value is contained in count\ntestset.drop(['datetime'], axis = 1, inplace = True)\n# get index of the time elements in unique list\n_, idx = np.unique(testset.time, return_inverse = True)\n# replace time feature with the index just computed\ntestset.time = idx\n# replace date with weekday\ntestset.date = [1 if x >= 0 and x < 6 else 0 for x in testset.date]\n# replace feature name\ntestset.rename(columns = {'date':'weekday'}, inplace = True)\n# remove features highly correlated\ntestset.drop(['temp'], axis = 1, inplace = True)\n# group time values into day segments\ntestset.time = [0 if x >= 0 and x < 6 else(1 if x > 5 and x < 13 else (2 if x > 12 and x < 19 else 3)) for x in testset.time]\n# testset quick view\ntestset.head()"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]