class_docstr: A tabular element type to allow convenient visualization of either
  a standard Python dictionary or a list of tuples
  (i.e. input suitable for an dict constructor).
  Tables store heterogeneous data with different labels.
  
  Dimension objects are also accepted as keys, allowing dimensional
  information (e.g. type and units) to be associated per heading.
class_docstr_tok: ["A","tabular","element","type","to","allow","convenient","visualization","of","either","a","standard","Python","dictionary","or","a","list","of","tuples","(","i.e",".","input","suitable","for","an","dict","constructor",")",".","Tables","store","heterogeneous","data","with","different","labels",".","Dimension","objects","are","also","accepted","as","keys",",","allowing","dimensional","information","(","e.g",".","type","and","units",")","to","be","associated","per","heading","."]
code: def reduce(self, dimensions=None, function=None, **reduce_map):
      raise NotImplementedError(
          "ItemTables are for heterogeneous data, which"
          "cannot be reduced."
      )
  
imports: import numpy
  import param
  from ..core import Dataset, Element, Tabular
  from ..core.dimension import Dimension, dimension_name
  from .selection import SelectionIndexExpr
label_desc: Use image node_id 7 for calling the ItemTable obj's underlying member method code with example usage: obj.reduce(dimensions, function) without return types