[{'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:# draw store 1 and store 10 sales distribution plot<br>import matplotlib.pyplot as plt<br>store_1 = train.loc[(train["Store"]==1)&(train[\'Sales\']>0), [\'Date\',"Sales"]]<br>store_10 = train.loc[(train["Store"]==10)&(train[\'Sales\']>0), [\'Date\',"Sales"]]<br>f = plt.figure(figsize=(18,10))<br>ax1 = f.add_subplot(211)<br>ax1.plot(store_1[\'Date\'], store_1[\'Sales\'], \'-\')<br>ax1.set_xlabel(\'Time\')<br>ax1.set_ylabel(\'Sales\')<br>ax1.set_title(\'Store 1 Sales Distribution\')<br><br>ax2 = f.add_subplot(212)<br>ax2.plot(store_10[\'Date\'], store_10[\'Sales\'], \'-\')<br>ax2.set_xlabel(\'Time\')<br>ax2.set_ylabel(\'Sales\')<br>ax2.set_title(\'Store 10 Sales Distribution\')'}, {'role': 'assistant', 'content': "['result_visualization']"}]