class_docstr: Plotting object allows for visualization of absolute group bias metrics and
  relative disparities calculated by Aequitas Group(), Bias(), and Fairness()
  class instances.
code: def iterate_subplots(axs, ncols, rows, ax_col, ax_row):
      ax_col += 1
  
      if (ax_col >= ncols) and ((ax_col + 1) % ncols) == 1:
          ax_row += 1
          ax_col = 0
  
      if rows == 1:
          current_subplot = axs[ax_col]
  
      elif ncols == 1:
          current_subplot = axs[ax_row]
          ax_row += 1
      else:
          current_subplot = axs[ax_row, ax_col]
  
      return current_subplot, ax_row, ax_col
  
imports: import logging
  import math
  import numpy
  import collections
  import seaborn
  import matplotlib.pyplot
  import matplotlib.colors
  import matplotlib.cm
  from aequitas import squarify_flipped
label_desc: Use image node_id 7 for calling the Plot obj's underlying member method code with example usage: obj.iterate_subplots(axs, ncols, rows, ax_col, ax_row) and returns: current_subplot,  ax_row,  ax_col