code: def feature_data(self):
      session = Session()
      metadata = (
          session.query(FeatureMetaData)
          .filter_by(
              entity_name=self.entity_name,
              feature_name=self.feature_name,
              version=self.version,
              s3_url=None,
          )
          .filter(
              FeatureMetaData.snapshot_at.between(
                  self.start_date, self.end_date
              )
          )
      )
      if metadata.count() == 0:
          return pandas.DataFrame()
  
      metadata_ids = [str(m.id) for m in metadata]
      feature_name = metadata[0].feature_name
      dtypes = metadata[0].feature_dtypes
      sql = """SELECT key, feature_data FROM features where feature_metadata_id in ({feature_metadata_ids})"""
      sql = sql.format(feature_metadata_ids=",".join(metadata_ids))
      df = lore.io.metadata.dataframe(
          sql, feature_metadata_ids=metadata_ids
      )
      if lore.io.metadata.adapter == "sqlite":
          key_df = pandas.io.json.json_normalize(
              df.key.apply(json.loads)
          )
      else:
          key_df = pandas.io.json.json_normalize(df.key)
      df.drop("key", axis=1, inplace=True)
      df = pandas.concat([df, key_df], axis=1)
      df = df.rename({"feature_data": feature_name}, axis=1)
      df = df.astype(dtypes)
      return df
  
file_path: lore/lore/features/db.py
imports: from abc import ABCMeta
  from datetime import datetime
  import lore.io
  from lore.features.base import BaseFeatureExporter, BaseFeatureImporter
  import lore.metadata
  from lore.metadata import FeatureMetaData
  from sqlalchemy.orm import sessionmaker, scoped_session
  import pandas
  from lore.util import convert_df_columns_to_json
  import json
label_desc: Use image node_id 1 for calling the DBFeatureImporter obj's underlying member method code with example usage: obj.feature_data() and returns: df, pandas