[{'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:dailyData["date"] = dailyData.datetime.apply(lambda x : x.split()[0])<br>dailyData["hour"] = dailyData.datetime.apply(lambda x : x.split()[1].split(":")[0])<br>dailyData["weekday"] = dailyData.date.apply(lambda dateString : calendar.day_name[datetime.strptime(dateString,"%Y-%m-%d").weekday()])<br>dailyData["month"] = dailyData.date.apply(lambda dateString : calendar.month_name[datetime.strptime(dateString,"%Y-%m-%d").month])<br>dailyData["season"] = dailyData.season.map({1: "Spring", 2 : "Summer", 3 : "Fall", 4 :"Winter" })<br>dailyData["weather"] = dailyData.weather.map({1: " Clear + Few clouds + Partly cloudy + Partly cloudy",\\\\<br>                                        2 : " Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist ", \\\\<br>                                        3 : " Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds", \\\\<br>                                        4 :" Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow + Fog " })'}, {'role': 'assistant', 'content': "['data_preprocessing']"}]