code: def add_text_to_model_importance_dendrogram(
      fig, hierarchical_importance_data
  ):
      res_fig = go.Figure(fig)
      for scatter in res_fig.data:
          k = np.where(
              hierarchical_importance_data["dropout_loss"]
              == scatter.x[1]
          )[0][0]
          x_cord = scatter.x[1]
          y_cord = np.mean(scatter.y[1:3])
          scatter.x = np.insert(scatter.x, 2, x_cord)
          scatter.y = np.insert(scatter.y, 2, y_cord)
          label = "{0:.2f}".format(
              hierarchical_importance_data["dropout_loss_change"][k]
          )
          scatter.mode = "lines+text"
          scatter["text"] = [None, None, label, None, None]
          scatter["textposition"] = "middle left"
  
      return res_fig
  
file_path: DALEX/python/dalex/dalex/aspect/_model_triplot/plot.py
imports: import numpy
  import plotly.graph_objects
  from copy import deepcopy
  from dalex import _theme, _global_utils
label_desc: Use image node_id 3 for calling a global function with example usage: add_text_to_model_importance_dendrogram(fig, hierarchical_importance_data) and returns: res_fig