[{'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:Reading = df3.Reading\nScience = df3.Science\nMath = df3.Math\nGDP = np.log(df3.GDPpc)\nplt.scatter(x = GDP, y = Reading, color = 'r')\nplt.title('PISA 2012 Reading scores vs. GDP per capita')\nplt.xlabel('GDP per capita (log)')\nplt.ylabel('PISA Reading Score')\nplt.show()\nplt.scatter(x = GDP, y = Math, color = 'b')\nplt.title('PISA 2012 Math scores vs. GDP per capita')\nplt.xlabel('GDP per capita (log)')\nplt.ylabel('PISA Math Score')\nplt.show()\nplt.scatter(x = GDP, y = Science, color = 'g')\nplt.title('PISA 2012 Science scores vs. GDP per capita')\nplt.xlabel('GDP per capita (log)')\nplt.ylabel('PISA Science Score')\nplt.show()"}, {'role': 'assistant', 'content': "['data_exploration']"}]