code: def test_replace_dataframe_different_dataframe_types():
      dask_es = EntitySet(id="dask_es")
  
      sessions = pd.DataFrame(
          {
              "id": [0, 1, 2, 3],
              "user": [1, 2, 1, 3],
              "time": [
                  pd.to_datetime("2019-01-10"),
                  pd.to_datetime("2019-02-03"),
                  pd.to_datetime("2019-01-01"),
                  pd.to_datetime("2017-08-25"),
              ],
              "strings": ["I am a string", "23", "abcdef ghijk", ""],
          },
      )
      sessions_dask = dd.from_pandas(sessions, npartitions=2)
      sessions_logical_types = {
          "id": Integer,
          "user": Integer,
          "time": Datetime,
          "strings": NaturalLanguage,
      }
      sessions_semantic_tags = {"user": "foreign_key"}
  
      dask_es.add_dataframe(
          dataframe_name="sessions",
          dataframe=sessions_dask,
          index="id",
          time_index="time",
          logical_types=sessions_logical_types,
          semantic_tags=sessions_semantic_tags,
      )
  
      with pytest.raises(
          TypeError, match="Incorrect DataFrame type used"
      ):
          dask_es.replace_dataframe("sessions", sessions)
  
imports: from datetime import datetime
  import numpy
  import pandas
  import pytest
  from woodwork.exceptions import TypeConversionError
  from woodwork.logical_types import Boolean, Categorical, Datetime, Double, Integer, NaturalLanguage
  from featuretools.entityset.entityset import LTI_COLUMN_NAME, EntitySet
  from featuretools.tests.testing_utils import to_pandas
  from featuretools.utils.gen_utils import Library, import_or_none, is_instance
label_desc: Use image node_id 46 for calling a global function with example usage: test_replace_dataframe_different_dataframe_types() without return types