[{'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:weather_2011_1 = df['weather'][df['weather'] == 1][df['year'] == 2011].value_counts()\nweather_2011_2 = df['weather'][df['weather'] == 2][df['year'] == 2011].value_counts()\nweather_2011_3 = df['weather'][df['weather'] == 3][df['year'] == 2011].value_counts()\n\nweather_2012_1 = df['weather'][df['weather'] == 1][df['year'] == 2012].value_counts()\nweather_2012_2 = df['weather'][df['weather'] == 2][df['year'] == 2012].value_counts()\nweather_2012_3 = df['weather'][df['weather'] == 3][df['year'] == 2012].value_counts()\nweather_2012_4 = df['weather'][df['weather'] == 4][df['year'] == 2012].value_counts()\n\nprint('weather_1 in 2011: {}'.format(int(weather_2011_1)))\nprint('weather_2 in 2011: {}'.format(int(weather_2011_2)))\nprint('weather_3 in 2011: {}'.format(int(weather_2011_3)))\nprint('--------------')\nprint('weather_1 in 2012: {}'.format(int(weather_2012_1)))\nprint('weather_2 in 2012: {}'.format(int(weather_2012_2)))\nprint('weather_3 in 2012: {}'.format(int(weather_2012_3)))\nprint('weather_4 in 2012: {}'.format(int(weather_2012_4)))\nprint('---------------')\ntotal_2011 = int(weather_2011_1) + int(weather_2011_2) + int(weather_2011_3)\ntotal_2012 = int(weather_2012_1) + int(weather_2012_2) + int(weather_2012_3) + int(weather_2012_4)\nprint('weather_1 in 2011: {:.0f}%'.format(int(weather_2011_1) / int(total_2011) * 100))\nprint('weather_2 in 2011: {:.0f}%'.format(int(weather_2011_2) / int(total_2011) * 100))\nprint('weather_3 in 2011: {:.0f}%'.format(int(weather_2011_3) / int(total_2011) * 100))\nprint('--------------')\nprint('weather_1 in 2012: {:.0f}%'.format(int(weather_2012_1) / int(total_2012) * 100))\nprint('weather_2 in 2012: {:.0f}%'.format(int(weather_2012_2) / int(total_2012) * 100))\nprint('weather_3 in 2012: {:.0f}%'.format(int(weather_2012_3) / int(total_2012) * 100))\nprint('weather_4 in 2012: {:.0f}%'.format(int(weather_2012_4) / int(total_2012) * 100))"}, {'role': 'assistant', 'content': "['data_exploration']"}]