class_docstr: Container class for stock datasets.
  
  Arguments:
      filename (str/list): name of the file to download
      url (str): url for dataset
      size (int/list): file size
      path (str): local path to place files
      subset_pct (float/int): percentage of data set to use for training
class_docstr_tok: ["Container","class","for","stock","datasets",".","Arguments",":","filename","(","str\/list",")",":","name","of","the","file","to","download","url","(","str",")",":","url","for","dataset","size","(","int\/list",")",":","file","size","path","(","str",")",":","local","path","to","place","files","subset_pct","(","float\/int",")",":","percentage","of","data","set","to","use","for","training"]
code: def __init__(self, filename, url, size, path=".", subset_pct=100):
      # parameters to use in dataset config serialization
      super(Dataset, self).__init__(name=None)
      self.filename = filename
      self.url = url
      self.size = size
      self.path = path
      self.subset_pct = subset_pct
      self._data_dict = None
      if subset_pct != 100:
          # placeholder to use partial data set
          raise NotImplemented(
              "subset percentage feature is not yet implemented"
          )
  
imports: from __future__ import division
  from future import standard_library
  from future.moves.urllib.request import Request, urlopen
  import logging
  import os
  import sys
  import zipfile
  from neon import NervanaObject, logger
  from neon.util.compat import PY3
label_desc: Use image node_id 1 to create a new Dataset object from inherited base classes: NervanaObject with example: obj = Dataset(filename, url, size, path, subset_pct)