[{'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:import numpy as np # linear algebra<br>import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)<br>import matplotlib.pyplot as plt<br>import seaborn as sns<br>from subprocess import check_output<br><br># Load and describe data<br># print(check_output(["ls", "../input"]).decode("utf8"))<br>df = pd.read_json(open("../input/train.json", "r"))<br>df[\'n_photos\'] = df[\'photos\'].apply(len)<br>df[\'n_features\'] = df[\'features\'].apply(len)<br>df[\'ilevel_categ\'] = df[\'interest_level\'].map({\'low\': 1, \'medium\': 2, \'high\': 3})<br>df["n_description_words"] = df["description"].apply(lambda x: len(x.split(" ")))<br>df.info()'}, {'role': 'assistant', 'content': 'data_preprocessing'}]