code: def test_columnar_convert_transform_columns():
      columns = {
          "x": np.complex128(1),
          "y": np.uint16(2),
          "z": np.float32(3.0),
      }
  
      dfs = {
          name: pd.DataFrame({"s": [0], "t": [1], "w": [w]}, index=[i])
          for i, (name, w) in enumerate(columns.items())
      }
  
      converter = ColumnarConverter(
          name="some_name",
          default_type="foo",
          type_column=None,
          column_defaults={},
          selected_columns={
              "s": "ss",
              "t": "tt",
              "w": "ww",
          },
          transform_columns={
              "w": lambda x: x + 1,
          },
      )
  
      ids, columns, type_info = converter.convert(dfs)
  
      assert columns["ww"][0] == 2
      assert columns["ww"][1] == 3
      assert columns["ww"][2] == 4
  
      _check_type_info(
          type_info,
          [
              ("x", _empty_array(1)),
              ("y", _empty_array(1)),
              ("z", _empty_array(1)),
          ],
      )
  
      np.testing.assert_array_equal(columns["ss"], 0)
      np.testing.assert_array_equal(columns["tt"], 1)
  
imports: import networkx
  import numpy
  import pandas
  import pytest
  from stellargraph.core.convert import ColumnarConverter, convert_nodes, convert_edges, from_networkx
  from stellargraph.core.indexed_array import IndexedArray
label_desc: Use image node_id 11 for calling a global function with example usage: test_columnar_convert_transform_columns() without return types