code: def pandas_data_frame():
      df = pd.DataFrame(
          {
              "feature1": pd.Series(np.arange(10.0), dtype="float64"),
              "feature2": pd.Series(np.arange(10), dtype="int64"),
              "feature3": pd.Series(
                  ["2020-10-30T03:43:21Z"] * 10, dtype="string"
              ),
              "feature4": pd.Series(
                  np.arange(5.0), dtype="float64"
              ),  # contains nan
          }
      )
      return df
  
imports: from __future__ import absolute_import
  import datetime
  import json
  import time
  import dateutil.parser
  from contextlib import contextmanager
  import boto3
  import numpy
  import pandas
  import pytest
  from pandas import DataFrame
  from sagemaker.feature_store.feature_utils import get_feature_group_as_dataframe
  from sagemaker.feature_store.feature_definition import FractionalFeatureDefinition, StringFeatureDefinition, ListCollectionType
  from sagemaker.feature_store.feature_group import FeatureGroup
  from sagemaker.feature_store.feature_store import FeatureStore
  from sagemaker.feature_store.inputs import FeatureValue, FeatureParameter, TableFormatEnum, Filter, ResourceEnum, Identifier, DeletionModeEnum, TtlDuration, OnlineStoreConfigUpdate, OnlineStoreStorageTypeEnum
  from sagemaker.feature_store.dataset_builder import JoinTypeEnum
  from sagemaker.session import get_execution_role, Session
  from tests.integ.timeout import timeout
  from urllib.parse import urlparse
label_desc: Use image node_id 7 for calling a global function with example usage: pandas_data_frame() and returns: df