code: def visualize(display_df):
      viridis = [
          "#440154",
          "#472c7a",
          "#3b518b",
          "#2c718e",
          "#21908d",
          "#27ad81",
          "#5cc863",
          "#aadc32",
          "#fde725",
      ]
      import altair as alt
  
      color_scale = alt.Scale(
          domain=(
              display_df.dropna().trending.min(),
              0,
              display_df.dropna().trending.max(),
          ),
          range=[viridis[0], viridis[len(viridis) // 2], viridis[-1]],
      )
  
      return (
          alt.Chart(display_df)
          .mark_circle()
          .encode(
              alt.X("variable"),
              alt.Y("term"),
              size="frequency",
              color=alt.Color("trending:Q", scale=color_scale),
          )
      )
  
label_desc: Use image node_id 1 for calling the BubbleDiachronicVisualization obj's underlying member method code with example usage: obj.visualize(display_df) and returns: alt