[{'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:#importing the libraries\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n# import seaborn as sns\nimport seaborn as sns; sns.set(style="ticks", color_codes=True)\n\nfrom datetime import datetime\nfrom scipy import stats\nfrom scipy.stats import norm, skew\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.preprocessing import MinMaxScaler\nfrom sklearn.preprocessing import LabelEncoder\nfrom sklearn.model_selection import train_test_split\nimport lightgbm as lgb\n\n# 100()\n# \npd.options.display.max_columns = None\npd.options.display.max_rows = 80\n\n# 2()\npd.options.display.float_format = \'{:.2f}\'.format\n%matplotlib inline\n#\nimport warnings\nwarnings.filterwarnings(\'ignore\')\n%matplotlib inline\''}, {'role': 'assistant', 'content': 'helper_functions'}]