code: def to_html(self, state_dict=None, add_header=True):
      args = self.get_state_args(state_dict)
      if args["display"] == "observed":
          fig = self.explainer.plot_y_vs_feature(
              args["col"],
              points=bool(args["points"]),
              winsor=args["winsor"],
              dropna=True,
              topx=args["cats_topx"],
              sort=args["cats_sort"],
              round=self.round,
              plot_sample=self.plot_sample,
          )
      elif args["display"] == "predicted":
          fig = self.explainer.plot_preds_vs_feature(
              args["col"],
              points=bool(args["points"]),
              winsor=args["winsor"],
              dropna=True,
              topx=args["cats_topx"],
              sort=args["cats_sort"],
              round=self.round,
              plot_sample=self.plot_sample,
          )
      else:
          fig = self.explainer.plot_residuals_vs_feature(
              args["col"],
              points=bool(args["points"]),
              winsor=args["winsor"],
              dropna=True,
              topx=args["cats_topx"],
              sort=args["cats_sort"],
              round=self.round,
              plot_sample=self.plot_sample,
          )
      fig.update_layout(margin=dict(t=40, b=40, l=40, r=40))
      html = to_html.card(
          to_html.fig(fig), title=self.title, subtitle=self.subtitle
      )
      if add_header:
          return to_html.add_header(html)
      return html
  
imports: import numpy
  import pandas
  import dash
  from dash import html, dcc, Input, Output, State
  from dash.exceptions import PreventUpdate
  import dash_bootstrap_components
  from ..dashboard_methods import *
  from ..None import to_html
label_desc: Use image node_id 3 for calling the RegressionVsColComponent obj's underlying member method code with example usage: obj.to_html(state_dict, add_header) and returns: html, to_html