class_docstr: Based on ffn's GroupStats with a few extra helper methods.
  
  Args:
      * backtests (list): List of backtests
  
  Attributes:
      * backtest_list (list): List of bactests in the same order as provided
      * backtests (dict): Dict of backtests by name
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docstr: :param backtest: (str, int) Backtest can be either a index (int) or the
          name (str)
  :param filter: (list, str) filter columns for specific columns. Filter
          is simply passed as is to DataFrame[filter], so use something
          that makes sense with a DataFrame.
  :return: (pd.DataFrame) DataFrame of weights
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code: def get_weights(self, backtest=0, filter=None):
      """
  
      :param backtest: (str, int) Backtest can be either a index (int) or the
              name (str)
      :param filter: (list, str) filter columns for specific columns. Filter
              is simply passed as is to DataFrame[filter], so use something
              that makes sense with a DataFrame.
      :return: (pd.DataFrame) DataFrame of weights
      """
  
      key = self._get_backtest(backtest)
  
      if filter is not None:
          data = self.backtests[key].weights[filter]
      else:
          data = self.backtests[key].weights
  
      return data
  
imports: from __future__ import division
  from copy import deepcopy
  import bt
  import ffn
  import pandas
  import numpy
  from matplotlib import pyplot
  import pyprind
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling the Result obj's underlying member method code with example usage: obj.get_weights(backtest, filter) and returns: data