class_docstr: Data model used for storing a batch of frames.
  Internally stored as a pandas DataFrame with columns
  "id" and "data".
  id: integer index of frame
  data: frame as np.array
  
  Arguments:
      frames (DataFrame): pandas Dataframe holding frames data
class_docstr_tok: ["Data","model","used","for","storing","a","batch","of","frames",".","Internally","stored","as","a","pandas","DataFrame","with","columns","''","id","''","and","``","data","''",".","id",":","integer","index","of","frame","data",":","frame","as","np.array","Arguments",":","frames","(","DataFrame",")",":","pandas","Dataframe","holding","frames","data"]
docstr: Return a column as numpy array
  
  Args:
      column_name (str): the name of the required column
  
  Returns:
      numpy.ndarray: the column data as a numpy array
docstr_tok: ["Return","a","column","as","numpy","array","Args",":","column_name","(","str",")",":","the","name","of","the","required","column","Returns",":","numpy.ndarray",":","the","column","data","as","a","numpy","array"]
code: def column_as_numpy_array(self, column_name: str) -> np.ndarray:
      """Return a column as numpy array
  
      Args:
          column_name (str): the name of the required column
  
      Returns:
          numpy.ndarray: the column data as a numpy array
      """
      return self._frames[column_name].to_numpy()
  
imports: from typing import Callable, Iterable, List, TypeVar, Union
  import numpy
  import pandas
  from evadb.expression.abstract_expression import ExpressionType
  from evadb.parser.alias import Alias
  from evadb.utils.generic_utils import PickleSerializer
  from evadb.utils.logging_manager import logger
label_desc: Use image node_id 5 for calling the Batch obj's underlying member method code with example usage: obj.column_as_numpy_array(column_name) and returns: self