[{'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:# Crrelation between revenue and feature (p)s\ndef numFeaturePlot():\n    features=(data.loc[:,\'P1\':\'P37\']).columns.tolist()\n    plt.figure(figsize=(35,18))\n    j=1\n    while j<len(features):\n        col=features[j-1]\n        plt.subplot(6,6,j)\n        sorted_grp = data.groupby(col)["revenue"].sum().sort_values(ascending=False).reset_index()\n        x_val = sorted_grp.index\n        y_val = sorted_grp[\'revenue\'].values\n        plt.scatter(x_val, y_val)\n        plt.xticks(rotation=60)\n        plt.xlabel(col, fontsize=20)\n        plt.ylabel(\'Revenue\', fontsize=20)\n        j+=1    \n    plt.tight_layout()\n    plt.show()\nnumFeaturePlot()\''}, {'role': 'assistant', 'content': "['result_visualization']"}]