code: def _concatenate_chunks(chunks: list[dict[int, ArrayLike]]) -> dict:
      """
      Concatenate chunks of data read with low_memory=True.
  
      The tricky part is handling Categoricals, where different chunks
      may have different inferred categories.
      """
      names = list(chunks[0].keys())
      warning_columns = []
  
      result: dict = {}
      for name in names:
          arrs = [chunk.pop(name) for chunk in chunks]
          # Check each arr for consistent types.
          dtypes = {a.dtype for a in arrs}
          non_cat_dtypes = {
              x for x in dtypes if not is_categorical_dtype(x)
          }
  
          dtype = dtypes.pop()
          if is_categorical_dtype(dtype):
              result[name] = union_categoricals(
                  arrs, sort_categories=False
              )
          else:
              result[name] = concat_compat(arrs)
              if len(non_cat_dtypes) > 1 and result[
                  name
              ].dtype == np.dtype(object):
                  warning_columns.append(str(name))
  
      if warning_columns:
          warning_names = ",".join(warning_columns)
          warning_message = " ".join(
              [
                  f"Columns ({warning_names}) have mixed types. "
                  f"Specify dtype option on import or set low_memory=False."
              ]
          )
          warnings.warn(
              warning_message,
              DtypeWarning,
              stacklevel=find_stack_level(),
          )
      return result
  
imports: from __future__ import annotations
  from collections import defaultdict
  from typing import TYPE_CHECKING, Hashable, Mapping, Sequence
  import warnings
  import numpy
  from pandas._libs import lib, parsers
  from pandas._typing import ArrayLike, DtypeArg, DtypeObj, ReadCsvBuffer
  from pandas.compat._optional import import_optional_dependency
  from pandas.errors import DtypeWarning
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import is_categorical_dtype, pandas_dtype
  from pandas.core.dtypes.concat import concat_compat, union_categoricals
  from pandas.core.indexes.api import ensure_index_from_sequences
  from pandas.io.common import dedup_names, is_potential_multi_index
  from pandas.io.parsers.base_parser import ParserBase, ParserError, is_index_col
label_desc: Use image node_id 1 for calling a global function with example usage: _concatenate_chunks(chunks) and returns: result