Interactive Panel App with `bind`#

An interactive app that filters penguins by species and body mass threshold using Panel widgets and setting up interactivity with pn.bind. The filtered data is visualized as a scatter plot.

import panel as pn
import hvplot.pandas  # noqa

df = hvplot.sampledata.penguins("pandas").dropna()

species_widget = pn.widgets.Select(
    name='Species',
    options=list(df['species'].unique()),
    width=200,
)

mass_widget = pn.widgets.IntSlider(
    name='Min Body Mass (g)',
    start=int(df['body_mass_g'].min()),
    end=int(df['body_mass_g'].max()),
    step=100,
    value=4000,
    width=200,
)

def plot_penguins(species, min_mass):
    subset = df[(df['species'] == species) & (df['body_mass_g'] >= min_mass)]
    return subset.hvplot.scatter(
        x='bill_length_mm',
        y='bill_depth_mm',
        color='body_mass_g',
        cmap='viridis_r',
        size=24,
        title=f'{species} Penguins (body mass ≥ {min_mass})',
        xlabel='Bill Length (mm)',
        ylabel='Bill Depth (mm)',
    )

plot = pn.bind(plot_penguins, species=species_widget, min_mass=mass_widget)

pn.Column(pn.Row(species_widget, mass_widget), plot)

Interactive Panel App with bind#

Interactive Panel App with `bind`#