Switching between categorical and continuous Dynamic Map coloring (not working)

hv_coloring.py

import holoviews as hv
import numpy as np
import pandas as pd
hv.extension("bokeh")

# Generate data
base_df = pd.DataFrame({
    "x": np.random.randn(100), "y": np.random.randn(100),
    "cat1": np.random.randint(0, 5, 100), "cat2": np.random.randint(0, 5, 100),
    "con1": np.random.randn(100), "con2": np.random.randn(100)})
base_df["cat1"], base_df["cat2"] = base_df["cat1"].astype(str), base_df["cat2"].astype(str).astype("category")

# Define callback
def gen_plot(symbol):
    plotdf = pd.DataFrame({"x": base_df["x"], "y": base_df["y"], "color": base_df[symbol]})
    return hv.Points(plotdf, vdims=["color"]).options(color_index="color")

# Show
hv.DynamicMap(gen_plot, kdims=["symbol"]).redim.values(symbol=["cat1", "cat2", "col1", "col2"])
# Note: I think there is some state here. Sometimes nothing happens if I choose a categorical coloring, sometimes all the points disappear

# Alternative, trying to be more explicit
def gen_plot2(symbol):
    plotdf = pd.DataFrame({"x": base_df["x"], "y": base_df["y"], "color": base_df[symbol]})
    if (plotdf["color"].dtype.name == "category") or (plotdf["color"].apply(type) == str).all():
        cmap = "Colorblind"
    else:
        cmap= "Viridis"
    return hv.Points(plotdf, vdims=["color"]).options(color_index="color", cmap=cmap)

# Show
hv.DynamicMap(gen_plot2, kdims=["symbol"]).redim.values(symbol=["cat1", "cat2", "con1", "con2"])