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: Creates Batch by combining two batches using some arithmetic expression.
docstr_tok: ["Creates","Batch","by","combining","two","batches","using","some","arithmetic","expression","."]
code: def combine_batches(
      cls, first: Batch, second: Batch, expression: ExpressionType
  ) -> Batch:
      """
      Creates Batch by combining two batches using some arithmetic expression.
      """
      if expression == ExpressionType.ARITHMETIC_ADD:
          return Batch(pd.DataFrame(first._frames + second._frames))
      elif expression == ExpressionType.ARITHMETIC_SUBTRACT:
          return Batch(pd.DataFrame(first._frames - second._frames))
      elif expression == ExpressionType.ARITHMETIC_MULTIPLY:
          return Batch(pd.DataFrame(first._frames * second._frames))
      elif expression == ExpressionType.ARITHMETIC_DIVIDE:
          return Batch(pd.DataFrame(first._frames / second._frames))
  
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 38 for calling the Batch obj's underlying member method code with example usage: obj.combine_batches(cls, first, second, expression) and returns: Batch, Batch, Batch, Batch