[{'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:#add date columns\nunion_data['day']=pd.to_datetime(union_data.datetime).dt.day\nunion_data['year']=pd.to_datetime(union_data.datetime).dt.year\nunion_data['month']=pd.to_datetime(union_data.datetime).dt.month\nunion_data['weekday']=pd.to_datetime(union_data.datetime).dt.weekday\nunion_data['date']=pd.to_datetime(union_data.datetime).dt.date\nunion_data['hour']=pd.to_datetime(union_data.datetime).dt.hour\nunion_data['year_season']=union_data.apply(lambda x:'{}_{}'.format(str(x['year']),str(x['season'])),axis=1)\nunion_data['year_month']=union_data.apply(lambda x:'{}_{}'.format(str(x['year']),str(x['month'])),axis=1)\n#missing data fill\nunion_data['windspeed']=union_data[['year','month','hour','windspeed']].groupby(['year','month','hour']).transform(lambda x:x.replace(0,np.median([i for i in x if i>0])))\nunion_data['windspeed']=pd.cut(union_data['windspeed'],bins=[0,20,60],labels=['0','1'])\n"}, {'role': 'assistant', 'content': 'data_preprocessing'}]