code: def _create_index(self, index_name):
      import numpy as np
  
      # Create feature vector table and raw input table.
      feat1 = np.array([[0, 0, 0]]).astype(np.float32)
      feat2 = np.array([[100, 100, 100]]).astype(np.float32)
      feat3 = np.array([[200, 200, 200]]).astype(np.float32)
  
      # Create table.
      execute_query_fetch_all(
          self.evadb,
          """create table if not exists testCreateIndexFeatTable (
                  feat NDARRAY FLOAT32(1,3)
              );""",
      )
  
      # Create pandas dataframe.
      feat_batch_data = Batch(
          pd.DataFrame(
              data={
                  "feat": [feat1, feat2, feat3],
              }
          )
      )
      feat_tb_entry = self.evadb.catalog().get_table_catalog_entry(
          "testCreateIndexFeatTable"
      )
      storage_engine = StorageEngine.factory(self.evadb, feat_tb_entry)
      storage_engine.write(feat_tb_entry, feat_batch_data)
  
      query = f"CREATE INDEX {index_name} ON testCreateIndexFeatTable (feat) USING FAISS;"
      execute_query_fetch_all(self.evadb, query)
  
imports: import unittest
  from pathlib import Path
  from test.util import create_sample_video, file_remove, get_evadb_for_testing
  import pandas
  import pytest
  from evadb.catalog.catalog_utils import get_video_table_column_definitions
  from evadb.executor.executor_utils import ExecutorError
  from evadb.models.storage.batch import Batch
  from evadb.server.command_handler import execute_query_fetch_all
  from evadb.storage.storage_engine import StorageEngine
label_desc: Use image node_id 3 for calling the DropObjectExecutorTest obj's underlying member method code with example usage: obj._create_index(index_name) without return types