code: def _data_to_frame(data, **kwargs) -> DataFrame:
      """
      Convert parsed data to Data Frame.
  
      This method will bind xml dictionary data of keys and values
      into named columns of Data Frame using the built-in TextParser
      class that build Data Frame and infers specific dtypes.
      """
  
      tags = next(iter(data))
      nodes = [list(d.values()) for d in data]
  
      try:
          with TextParser(nodes, names=tags, **kwargs) as tp:
              return tp.read()
      except ParserError:
          raise ParserError(
              "XML document may be too complex for import. "
              "Try to flatten document and use distinct "
              "element and attribute names."
          )
  
imports: from __future__ import annotations
  import io
  from typing import Any, Callable, Sequence
  from pandas._libs import lib
  from pandas._typing import TYPE_CHECKING, CompressionOptions, ConvertersArg, DtypeArg, DtypeBackend, FilePath, ParseDatesArg, ReadBuffer, StorageOptions, XMLParsers
  from pandas.compat._optional import import_optional_dependency
  from pandas.errors import AbstractMethodError, ParserError
  from pandas.util._decorators import doc
  from pandas.util._validators import check_dtype_backend
  from pandas.core.dtypes.common import is_list_like
  from pandas.core.shared_docs import _shared_docs
  from pandas.io.common import file_exists, get_handle, infer_compression, is_fsspec_url, is_url, stringify_path
  from pandas.io.parsers import TextParser
label_desc: Use image node_id 3 for calling a global function with example usage: _data_to_frame(data) and returns: tp