[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:LA = (35.0569, -118.25)\nBeverly_Hills = (34.073056, -118.399444)\n\n#d_to_LA = np.sqrt((trainHouses["latitude"] - LA[0])**2 + (trainHouses["longitude"] - LA[1])**2)\nd_to_LA = getDistanceFromLatLng(trainHouses["latitude"], trainHouses["longitude"], LA[0], LA[1])\n#d_to_BH = np.sqrt((trainHouses["latitude"] - Beverly_Hills[0])**2 + (trainHouses["longitude"] - Beverly_Hills[1])**2)\nd_to_BH = getDistanceFromLatLng(trainHouses["latitude"], trainHouses["longitude"], Beverly_Hills[0], Beverly_Hills[1])\n\nplt.hist(d_to_LA, bins=100)\nplt.show()\nplt.hist2d(d_to_LA, trainHouses["median_house_value"], bins=100, norm=mcolors.PowerNorm(0.15))\nplt.show()\n\nplt.hist(d_to_BH, bins=100)\nplt.show()\nplt.hist2d(d_to_BH, trainHouses["median_house_value"], bins=100, norm=mcolors.PowerNorm(0.15))\nplt.show()'}, {'role': 'assistant', 'content': 'result_visualization'}]