code: def rebalance(
      df_or_series,
      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.
      """
      axis = validate_axis(axis, df_or_series)
      if num_partitions is None:
          factor = factor if factor is not None else 1.2
  
      op = DataFrameRebalance(
          input=df_or_series,
          factor=factor,
          axis=axis,
          num_partitions=num_partitions,
          reassign_worker=reassign_worker,
      )
      return op(df_or_series)
  
file_path: mars/mars/dataframe/base/rebalance.py
imports: from ...None import opcodes
  from ...serialization.serializables import KeyField, Float64Field, Int64Field
  from ...tensor.base.rebalance import RebalanceMixin
  from ..core import INDEX_TYPE
  from ..initializer import DataFrame, Series, Index
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import validate_axis
label_desc: Use image node_id 1 for calling a global function with example usage: rebalance(df_or_series, factor, axis, num_partitions, reassign_worker) and returns: op