new_contents: from __future__ import division
  from collections import defaultdict
  from itertools import combinations
  import numpy as np
  from base_sample import BaseSample
  
  
  
  class SimpleRandomization(BaseSample):
      
      def __init__(self, data_frame, number_arms=2):
          super(SimpleRandomization, self).__init__(data_frame, number_arms)
  
  
      def randomize(self):
          '''
          Simple randomization to randomly assign participants to arm of study
          '''
          
          # Add arm assignment column to dataframe or re-initialize to nan
          self.data['arm_assignment'] = np.ones(len(self.data))*np.nan         
          # Grab array of indicies
          df_inds = self.data.index.values        
          
          n_pop = len(df_inds)
          
          while len(df_inds) >0:
              
              # Loop over arms
              for arm in range(1,self.n_arms+1):
                  
                  # Randomly choose participant
                  random_ind = np.random.choice(df_inds)
                  # Assign random participant to arm
                  self.data['arm_assignment'].loc[random_ind]=arm
                  # Remove participant from list
                  del_ind = np.where(df_inds == random_ind)
                  df_inds = np.delete(df_inds, del_ind)
                  if len(df_inds)==0: 
                      break
          
          return self.data
subject: Add simple randomization