class_docstr: A column of data that's been concretely bound to a particular dataset.
  
  Instances of this class are dynamically created upon access to attributes
  of DataSets (for example, USEquityPricing.close is an instance of this
  class).
  
  Attributes
  ----------
  dtype : numpy.dtype
      The dtype of data produced when this column is loaded.
  latest : catalyst.pipeline.data.Factor or catalyst.pipeline.data.Filter
      A Filter, Factor, or Classifier computing the most recently known value
      of this column on each date.
  
      Produces a Filter if self.dtype == ``np.bool_``.
      Produces a Classifier if self.dtype == ``np.int64``
      Otherwise produces a Factor.
  dataset : catalyst.pipeline.data.DataSet
      The dataset to which this column is bound.
  name : str
      The name of this column.
code: def _init(self, dataset, name, *args, **kwargs):
      self._dataset = dataset
      self._name = name
      return super(BoundColumn, self)._init(*args, **kwargs)
  
imports: from functools import total_ordering
  from six import iteritems, with_metaclass
  from catalyst.pipeline.classifiers import Classifier, Latest
  from catalyst.pipeline.factors import Factor, Latest
  from catalyst.pipeline.filters import Filter, Latest
  from catalyst.pipeline.sentinels import NotSpecified
  from catalyst.pipeline.term import AssetExists, LoadableTerm, validate_dtype
  from catalyst.utils.input_validation import ensure_dtype
  from catalyst.utils.numpy_utils import NoDefaultMissingValue
  from catalyst.utils.preprocess import preprocess
label_desc: Use image node_id 2 for calling the BoundColumn obj's underlying member method code with example usage: obj._init(dataset, name) and returns: super