code: def test_concat_join_many_df_and_empty_df(
      ignore_index, sort, join, axis
  ):
      # no duplicate columns
      pdf1 = pd.DataFrame(
          {
              "x": range(10),
              "y": list(map(float, range(10))),
              "z": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
          }
      )
      pdf2 = pd.DataFrame(
          {"l": range(10, 20), "m": list(map(float, range(10, 20)))}
      )
      pdf3 = pd.DataFrame(
          {"j": [1, 2], "k": [1, 2], "s": [1, 2], "t": [1, 2]}
      )
      pdf_empty1 = pd.DataFrame()
  
      gdf1 = gd.from_pandas(pdf1)
      gdf2 = gd.from_pandas(pdf2)
      gdf3 = gd.from_pandas(pdf3)
      gdf_empty1 = gd.from_pandas(pdf_empty1)
  
      assert_eq(
          pd.concat(
              [pdf1, pdf2, pdf3, pdf_empty1],
              sort=sort,
              join=join,
              ignore_index=ignore_index,
              axis=axis,
          ),
          gd.concat(
              [gdf1, gdf2, gdf3, gdf_empty1],
              sort=sort,
              join=join,
              ignore_index=ignore_index,
              axis=axis,
          ),
          check_index_type=False,
      )
  
imports: from decimal import Decimal
  import numpy
  import pandas
  import pytest
  import cudf
  from cudf.api.types import is_categorical_dtype
  from cudf.core._compat import PANDAS_GE_150, PANDAS_LT_140
  from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype
  from cudf.testing._utils import assert_eq, assert_exceptions_equal
label_desc: Use image node_id 27 for calling a global function with example usage: test_concat_join_many_df_and_empty_df(ignore_index, sort, join, axis) without return types