class_docstr: Interface for simple dictionary-based dataset format. The dictionary
  keys correspond to the column (i.e. dimension) names and the values
  are collections representing the values in that column.
class_docstr_tok: ["Interface","for","simple","dictionary-based","dataset","format",".","The","dictionary","keys","correspond","to","the","column","(","i.e",".","dimension",")","names","and","the","values","are","collections","representing","the","values","in","that","column","."]
code: def redim(cls, dataset, dimensions):
      all_dims = dataset.dimensions()
      renamed = []
      for k, v in dataset.data.items():
          if k in dimensions:
              k = dimensions[k].name
          elif k in all_dims:
              k = dataset.get_dimension(k).name
          renamed.append((k, v))
      return dict(renamed)
  
imports: from collections import OrderedDict, defaultdict
  import numpy
  from ..None import util
  from ..dimension import dimension_name
  from ..element import Element
  from ..ndmapping import NdMapping, item_check, sorted_context
  from ..util import isscalar
  from .interface import DataError, Interface
label_desc: Use image node_id 10 for calling the DictInterface obj's underlying member method code with example usage: obj.redim(cls, dataset, dimensions) and returns: dict