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data (dict): A nested JSON data structure.\n - key_paths (List[str]): Paths to keys in the JSON structure.\n - value_types (List[type]): Types to categorize the extracted values.\n \n Requirements:\n - json\n - collections\n - itertools\n - pandas\n - numpy\n \n Example:\n >>> data = {\n ... \"root\": {\n ... \"child1\": {\"name\": \"Alice\", \"age\": 30, \"is_student\": False},\n ... \"child2\": {\"name\": \"Bob\", \"age\": 25, \"is_student\": True},\n ... \"child3\": {\"name\": \"Charlie\", \"age\": 35, \"is_student\": False},\n ... \"child4\": {\"name\": \"David\", \"age\": 22, \"is_student\": True}\n ... }\n ... }\n >>> key_paths = [\"root.child1.age\", \"root.child2.is_student\", \"root.child3.name\"]\n >>> value_types = [int, bool, str]\n >>> result = analyze_nested_json(data, key_paths, value_types)\n >>> print(result)\n {\n \\'int\\': [30, 25, 35, 22],\n \\'bool\\': [False, True, False, True],\n \\'str\\': [\\'Alice\\', \\'Bob\\', \\'Charlie\\', \\'David\\']\n }\n \n Returns:\n dict: A dictionary mapping types to lists of extracted values.\n \"\"\"\n \n def get_value_from_path(data, path):\n keys = path.split(\\'.\\')\n value = data\n for key in keys:\n value = value.get(key)\n if value is None:\n return None\n return value\n \n categorized_values = defaultdict(list)\n \n for key_path, value_type in zip(key_paths, value_types):\n value = get_value_from_path(data, key_path)\n if isinstance(value, value_type):\n categorized_values[str(value_type)].append(value)\n \n return dict(categorized_values)\n\n' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a Python expert.\nReturn ONLY the function implementation with no additional text or explanations.\n\nHere are some examples:\n\nex.1\n\n\nquery:\nwrite a function def analyze_nested_json(data, key_paths, value_types) to:\nAnalyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n\nThe function should output with:\ndict: A dictionary mapping types to lists of extracted values.\n\nYou should start with:\n\\`\\`\\`\nimport json\nimport defaultdict\nimport chain\nimport pandas as pd\nimport numpy as np\ndef analyze_nested_json(data, key_paths, value_types) \\`\\`\\`\n\n\nresponse:\nimport json\nfrom collections import defaultdict\nfrom itertools import chain\nimport pandas as pd\nimport numpy as np\n\ndef analyze_nested_json(data, key_paths, value_types):\n \"\"\"\n Analyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n \n Parameters:\n - data (dict): A nested JSON data structure.\n - key_paths (List[str]): Paths to keys in the JSON structure.\n - value_types (List[type]): Types to categorize the extracted values.\n \n Requirements:\n - json\n - collections\n - itertools\n - pandas\n - numpy\n \n Example:\n >>> data = {\n ... \"root\": {\n ... \"child1\": {\"name\": \"Alice\", \"age\": 30, \"is_student\": False},\n ... \"child2\": {\"name\": \"Bob\", \"age\": 25, \"is_student\": True},\n ... \"child3\": {\"name\": \"Charlie\", \"age\": 35, \"is_student\": False},\n ... \"child4\": {\"name\": \"David\", \"age\": 22, \"is_student\": True}\n ... }\n ... }\n >>> key_paths = [\"root.child1.age\", \"root.child2.is_student\", \"root.child3.name\"]\n >>> value_types = [int, bool, str]\n >>> result = analyze_nested_json(data, key_paths, value_types)\n >>> print(result)\n {\n \\'int\\': [30, 25, 35, 22],\n \\'bool\\': [False, True, False, True],\n \\'str\\': [\\'Alice\\', \\'Bob\\', \\'Charlie\\', \\'David\\']\n }\n \n Returns:\n dict: A dictionary mapping types to lists of extracted values.\n \"\"\"\n \n def get_value_from_path(data, path):\n keys = path.split(\\'.\\')\n value = data\n for key in keys:\n value = value.get(key)\n if value is None:\n return None\n return value\n \n categorized_values = defaultdict(list)\n \n for key_path, value_type in zip(key_paths, value_types):\n value = get_value_from_path(data, key_path)\n if isinstance(value, value_type):\n categorized_values[str(value_type)].append(value)\n \n return dict(categorized_values)\n\n<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 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