[{'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:print("Fatalities / Public")\nplt.figure(figsize=(30,30))\nfor i in range(30):\n    plt.subplot(5,6,i+1)\n    idx = i * 10\n    df_interest = df_preds[df_preds[\'place_id\']==places_sort[idx]].reset_index(drop=True)\n    tmp = df_interest[\'fatal/day\'].values\n    tmp = np.cumsum(tmp)\n    sns.lineplot(x=df_interest[\'day\'], y=tmp, label=\'pred\')\n    df_interest2 = df_traintest10[(df_traintest10[\'place_id\']==places_sort[idx]) & (df_traintest10[\'day\']<=day_before_private)].reset_index(drop=True)\n    sns.lineplot(x=df_interest2[\'day\'].values, y=df_interest2[\'Fatalities\'].values, label=\'true\')\n    plt.title(places_sort[idx])\nplt.show()\''}, {'role': 'assistant', 'content': "['result_visualization']"}]