class_docstr: A BarDataSeries that will build on top of another, higher frequency, BarDataSeries.
  Resampling will take place as new values get pushed into the dataseries being resampled.
  
  :param dataSeries: The DataSeries instance being resampled.
  :type dataSeries: :class:`pyalgotrade.dataseries.bards.BarDataSeries`
  :param frequency: The grouping frequency in seconds. Must be > 0.
  :param maxLen: The maximum number of values to hold.
      Once a bounded length is full, when new items are added, a corresponding number of items are discarded
      from the opposite end.
  :type maxLen: int.
  
  .. note::
      * Supported resampling frequencies are:
          * Less than bar.Frequency.DAY
          * bar.Frequency.DAY
          * bar.Frequency.MONTH
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code: def __init__(self, dataSeries, frequency, maxLen=None):
      if not isinstance(dataSeries, bards.BarDataSeries):
          raise Exception(
              "dataSeries must be a dataseries.bards.BarDataSeries instance"
          )
  
      super(ResampledBarDataSeries, self).__init__(maxLen)
      self.initDSResampler(dataSeries, frequency)
  
imports: import abc
  import six
  from pyalgotrade import dataseries
  from pyalgotrade.dataseries import bards
  from pyalgotrade import bar
  from pyalgotrade import resamplebase
label_desc: Use image node_id 1 to create a new ResampledBarDataSeries object from inherited base classes: bards, DSResampler with example: obj = ResampledBarDataSeries(dataSeries, frequency, maxLen)