[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:x = [a for a in clean_hospital_read_df['Number of Discharges'][81:-3]]\ny = list(clean_hospital_read_df['Excess Readmission Ratio'][81:-3])\nfig, ax = plt.subplots(figsize=(8,5))\nax.scatter(x, y,alpha=0.2)\nax.fill_between([0,350], 1.15, 2, facecolor='red', alpha = .15, interpolate=True)\nax.fill_between([800,2500], .5, .95, facecolor='green', alpha = .15, interpolate=True)\nax.set_xlim([0, max(x)])\nax.set_xlabel('Number of discharges', fontsize=12)\nax.set_ylabel('Excess rate of readmissions', fontsize=12)\nax.set_title('Scatterplot of number of discharges vs. excess rate of readmissions', fontsize=14)\nax.grid(True)\nfig.tight_layout()"}, {'role': 'assistant', 'content': "['data_exploration']"}]