docstr: Test that Arrow incompatible columns are disabled (configured as non-editable).
docstr_tok: ["Test","that","Arrow","incompatible","columns","are","disabled","(","configured","as","non-editable",")","."]
code: def test_apply_data_specific_configs_disables_columns(self):
      """Test that Arrow incompatible columns are disabled (configured as non-editable)."""
      columns_config: ColumnConfigMapping = {}
      data_df = pd.DataFrame(
          {
              "a": pd.Series([1, 2]),
              "b": pd.Series(["foo", "bar"]),
              "c": pd.Series([1, "foo"]),  # Incompatible
              "d": pd.Series([1 + 2j, 3 + 4j]),  # Incompatible
          }
      )
  
      apply_data_specific_configs(
          columns_config,
          data_df,
          DataFormat.PANDAS_DATAFRAME,
          check_arrow_compatibility=True,
      )
      self.assertNotIn("a", columns_config)
      self.assertNotIn("b", columns_config)
      self.assertTrue(columns_config["c"]["disabled"])
      self.assertTrue(columns_config["d"]["disabled"])
  
imports: from __future__ import annotations
  import datetime
  import unittest
  from decimal import Decimal
  import numpy
  import pandas
  import pyarrow
  from parameterized import parameterized
  from streamlit.elements.lib.column_config_utils import _EDITING_COMPATIBILITY_MAPPING, INDEX_IDENTIFIER, ColumnConfigMapping, ColumnConfigMappingInput, ColumnDataKind, _convert_column_config_to_json, _determine_data_kind, _determine_data_kind_via_arrow, _determine_data_kind_via_inferred_type, _determine_data_kind_via_pandas_dtype, apply_data_specific_configs, determine_dataframe_schema, is_type_compatible, process_config_mapping, update_column_config
  from streamlit.elements.lib.column_types import ColumnConfig
  from streamlit.errors import StreamlitAPIException
  from streamlit.type_util import DataFormat
label_desc: Use image node_id 13 for calling the ColumnConfigUtilsTest obj's underlying member method code with example usage: obj.test_apply_data_specific_configs_disables_columns() without return types