[{'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:fig = pyplot.figure() # Create matplotlib figure\nax = fig.add_subplot(111) # Create matplotlib axes\nax2 = ax.twinx() # Create another axes that shares the same x-axis as ax.\nwidth = 0.4\nle_c[\'LEatBirth\'].plot(kind=\'bar\', color=\'red\', ax=ax, width=width, position=1, figsize=(14,7))\nle_c[\'Commitments\'].plot(kind=\'bar\', color=\'blue\', ax=ax2, width=width, position=0, figsize=(14,7))\nax.set_ylabel(\'Life Expectancy at Birth\', color=\'red\')\nax2.set_ylabel(\'Commitments (US Millions)\', color=\'blue\')\npyplot.xticks([], "")\npyplot.xlabel(\'Countries\')\npyplot.show()'}, {'role': 'assistant', 'content': "['data_exploration']"}]