code: from llama_index import SimpleDirectoryReader
  import logging
  import sys
  from pathlib import Path
  from llama_index import download_loader
  
  PandasExcelReader = download_loader("PandasExcelReader")
  
  loader = PandasExcelReader(pandas_config={"header": 0})
  documents = loader.load_data(file=Path('src/data/train_dataset.xlsx'))
  print(f'Loaded {len(documents)} docs')
  print(type(documents[0]))
  '''
  db = DatabaseReader(
      scheme="postgresql",  # Database Scheme
      host="localhost",  # Database Host
      port="5432",  # Database Port
      user="postgres",  # Database User
      password="FakeExamplePassword",  # Database Password
      dbname="postgres",  # Database Name
  )
  
  print(type(db))
  # DatabaseReader available method:
  print(type(db.load_data))
  
  ### SQLDatabase class ###
  # db.sql is an instance of SQLDatabase:
  print(type(db.sql_database))
  # SQLDatabase available methods:
  print(type(db.sql_database.from_uri))
  print(type(db.sql_database.get_single_table_info))
  print(type(db.sql_database.get_table_columns))
  print(type(db.sql_database.get_table_info))
  print(type(db.sql_database.get_table_names))
  print(type(db.sql_database.insert_into_table))
  print(type(db.sql_database.run))
  print(type(db.sql_database.run_sql))
  # SQLDatabase available properties:
  print(type(db.sql_database.dialect))
  print(type(db.sql_database.engine))
  print(type(db.sql_database.table_info))
  
  query = f"""
      SELECT
          CONCAT(name, ' is ', age, ' years old.') AS text
      FROM public.users
      WHERE age >= 18
      """
  
  documents = db.load_data(query=query)
  
  # Display type(documents) and documents
  # type(documents) must return <class 'list'>
  print(type(documents))
  
  # Documents must return a list of Document objects
  print(documents)
  
  
  documents = SimpleDirectoryReader('./data').load_data()
  
  index = VectorStoreIndex.from_documents(documents)
  '''
apis: llama_index.download_loader
extract_api: [((164, 200), 'llama_index.download_loader', 'download_loader', (['"""PandasExcelReader"""'], {}), "('PandasExcelReader')\n", (179, 200), False, 'from llama_index import download_loader\n'), ((295, 330), 'pathlib.Path', 'Path', (['"""src/data/train_dataset.xlsx"""'], {}), "('src/data/train_dataset.xlsx')\n", (299, 330), False, 'from pathlib import Path\n')]