[{'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:a=[]<br>b=[]<br>c=[]<br>building_level={}<br>for j in train_df[\'manager_id\'].values:<br>    building_level[j]=[0,0,0]<br>for j in range(train_df.shape[0]):<br>    temp=train_df.iloc[j]<br>    if temp[\'interest_level\']==\'low\':<br>        building_level[temp[\'manager_id\']][0]+=1<br>    if temp[\'interest_level\']==\'medium\':<br>        building_level[temp[\'manager_id\']][1]+=1<br>    if temp[\'interest_level\']==\'high\':<br>        building_level[temp[\'manager_id\']][2]+=1<br><br>for i in test_df[\'manager_id\'].values:<br>    if i not in building_level.keys():<br>        a.append(np.nan)<br>        b.append(np.nan)<br>        c.append(np.nan)<br>    else:<br>        a.append(building_level[i][0]*1.0/sum(building_level[i]))<br>        b.append(building_level[i][1]*1.0/sum(building_level[i]))<br>        c.append(building_level[i][2]*1.0/sum(building_level[i]))<br>test_df[\'manager_level_low\']=a<br>test_df[\'manager_level_medium\']=b<br>test_df[\'manager_level_high\']=c<br><br><br>features_to_use.append(\'manager_level_low\') <br>features_to_use.append(\'manager_level_medium\') <br>features_to_use.append(\'manager_level_high\')<br>categorical = ["display_address", "manager_id", "building_id", "street_address"]<br>'}, {'role': 'assistant', 'content': 'data_preprocessing'}]