code: def task_percentages(data, n_tasks=9):
      
      pdata = deepcopy(data)
      for i in range(len(data)):
          for j in range(len(data[0])):
              percentages = [0.0]*n_tasks
              for k in range(len(data[i][j])):
                  b_ind = data[i][j][k].find("b")
                  for l in range(b_ind+1, len(data[i][j][k])):
                      percentages[l-2] += int(data[i][j][k][l])
              for p in range(len(percentages)):
                  percentages[p] /= len(data[i][j])
              pdata[i][j] = percentages
  
      return pdata
docs: Takes a 3D array of strings representing binary numbers and calculates
      the percentage of organisms in each cell (across multiple files)
      that were doing a given task.
  
      Returns an m x n x n_tasks array indicating the percentages of organisms
      at each location (across the 3rd dimension) that were doing each task.