[{'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:figure, ((ax1,ax2,ax3),(ax4,ax5,ax6)) = plt.subplots(nrows = 2, ncols = 3)\nfigure.set_size_inches(18,10)\n\nsns.barplot(data=df_train, x = "year", y = "count", ax = ax1)\nsns.barplot(data=df_train, x = "month", y = "count", ax = ax2)\nsns.barplot(data=df_train, x = "day", y = "count", ax = ax3)\nsns.barplot(data=df_train, x = "hour", y = "count", ax = ax4)\nsns.barplot(data=df_train, x = "minute", y = "count", ax = ax5)\nsns.barplot(data=df_train, x = "second", y = "count", ax = ax6)\n\nax1.set(ylabel = "count", title = "Rental amount by year")\nax2.set(ylabel = "count", title = "Rental amount by month")\nax3.set(ylabel = "count", title = "Rental amount by day")\nax4.set(ylabel = "count", title = "Rental amount by hour")\n\n#       barplot   .\n#    11 12     . \n#         .\n#   1~19  .  test    .\n#   8 5, 6  ,      .'}, {'role': 'assistant', 'content': "['result_visualization']"}]