[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:df1 = df.groupby(['BOROUGH'],sort = False)['VEHICLE 1 TYPE','VEHICLE 2 TYPE','VEHICLE 3 TYPE','VEHICLE 4 TYPE'].count().reset_index()\ndf2= DataFrame() #creating an empty dataframe\ndf2['BOROUGH'] = df1['BOROUGH']  # copying Borough column to the new dataframe\ndf2['One_Vehicle_Involved'] = df1['VEHICLE 1 TYPE'] - df1['VEHICLE 2 TYPE'] #count of one Vehicle involved\ndf2['Two_Vehicles_Involved'] = df1['VEHICLE 2 TYPE'] - df1['VEHICLE 3 TYPE'] #count of two Vehicles involved\ndf2['Three_Vehicles_Involved'] = df1['VEHICLE 3 TYPE'] - df1['VEHICLE 4 TYPE'] # count of three Vehicles involved\ndf2['More_Vehicle_Involved'] = df1['VEHICLE 4 TYPE'] #count of more Vehicles involved\ndf2.set_index('BOROUGH', inplace = True)\ndf2"}, {'role': 'assistant', 'content': 'data_preprocessing'}]