code: def rebalance(
      tensor,
      factor=None,
      axis=0,
      num_partitions=None,
      reassign_worker=True,
  ):
      """
      Make Data more balanced across entire cluster.
  
      Parameters
      ----------
      factor : float
          Specified so that number of chunks after balance is
          total CPU count of cluster * factor.
      axis : int
          The axis to rebalance.
      num_partitions : int
          Specified so the number of chunks are at most
          num_partitions.
      reassign_worker : bool
          If True, workers will be reassigned.
  
      Returns
      -------
      Series or DataFrame
          Result of DataFrame or Series after rebalanced.
      """
      if num_partitions is None:
          factor = factor if factor is not None else 1.2
  
      op = TensorRebalance(
          input=tensor,
          factor=factor,
          axis=axis,
          num_partitions=num_partitions,
          reassign_worker=reassign_worker,
      )
      return op(tensor)
  
imports: from ...None import opcodes
  from ...core import recursive_tile
  from ...core.context import get_context
  from ...serialization.serializables import KeyField, Float64Field, Int64Field
  from ...tensor.datasource import tensor
  from ...utils import has_unknown_shape, ceildiv
  from ..operands import TensorOperandMixin, TensorOperand
label_desc: Use image node_id 1 for calling a global function with example usage: rebalance(tensor, factor, axis, num_partitions, reassign_worker) and returns: op