[{'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:@info\ndef log_transf(df):\n    # log transformation function to remove skeew\n    df.Sales     = np.log1p(df.Sales)\n    df.Customers = np.log1p(df.Customers)\n    return df\n\n@info\ndef remove_outliers(df,column='Sales'):\n    # interquntile approach to remove outliers\n    q1  = df[column].quantile(0.2)\n    q3  = df[column].quantile(0.8)\n    iqr = q3-q1\n    iqr_lower = q1 - 1.5*iqr\n    iqr_upper = q3 + 1.5*iqr\n    \n    df = df.loc[(df[column] > iqr_lower) & (df[column]< iqr_upper),:]\n    return df"}, {'role': 'assistant', 'content': 'data_preprocessing'}]