code: def extra_session_df(es):
      row_values = {
          "customer_id": 2,
          "device_name": "PC",
          "device_type": 0,
          "id": 6,
      }
      row = pd.DataFrame(row_values, index=pd.Index([6], name="id"))
      df = to_pandas(es["sessions"])
      df = pd.concat([df, row]).sort_index()
      if es.dataframe_type == Library.DASK:
          df = dd.from_pandas(df, npartitions=3)
      elif es.dataframe_type == Library.SPARK:
          # Spark can't handle object dtypes
          df = df.astype("string")
          df = ps.from_pandas(df)
      return df
  
imports: from datetime import datetime
  import pandas
  import pytest
  from woodwork.logical_types import Categorical, Datetime, Integer
  from featuretools.entityset.entityset import LTI_COLUMN_NAME
  from featuretools.tests.testing_utils import to_pandas
  from featuretools.utils.gen_utils import Library, import_or_none
label_desc: Use image node_id 5 for calling a global function with example usage: extra_session_df(es) and returns: df