Hi @eudoxos
Welcome to the community. The trick is to bind to the selection parameter. Unfortunately the selected_dataframe is just a normal property and not a parameter that can be bound to.
import panel as pn
import hvplot.pandas
import pandas as pd
import numpy as np
pn.extension(sizing_mode="stretch_width")
lookup = {0: "A", 1: "B", 2: "C"}
pars = pd.DataFrame(
{"name": ["A", "B", "C"], "period": [1, 0.5, 0.3], "amplitude": [0.3, 0.4, 0.1]}
)
xx = np.linspace(0, 1, 100)
arr = pars["amplitude"].to_numpy() * np.sin(
np.outer(2 * np.pi * xx, 1.0 / pars["period"].to_numpy())
)
curves = pd.DataFrame(dict([(pars["name"][i], arr[:, i]) for i in range(0, 3)]), index=xx)
def compute_plot(selection):
if not selection:
selection_df = curves
else:
selection = [lookup[i] for i in selection]
selection_df = curves[selection]
return selection_df.hvplot(grid=True)
tabedit = pn.widgets.Tabulator(
value=pars, show_index=False, selectable=True, disabled=True, theme="site", height=140
)
plot = pn.bind(compute_plot, selection=tabedit.param.selection)
pn.template.FastListTemplate(
site="Awesome Panel", title="Table Selection", main=[tabedit, plot]
).servable()