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import panel as pn
import hvplot.pandas
# Load Data
from bokeh.sampledata.autompg import autompg_clean as df
# Make DataFrame Pipeline Interactive
idf = df.interactive()
# Define Panel widgets
cylinders = pn.widgets.IntSlider(name='Cylinders', start=4, end=8, step=2)
mfr = pn.widgets.ToggleGroup(
name='MFR',
options=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
value=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
button_type='success')
yaxis = pn.widgets.RadioButtonGroup(
name='Y axis',
options=['hp', 'weight'],
button_type='success'
)
# Combine pipeline and widgets
ipipeline = (
idf[
(idf.cyl == cylinders) &
(idf.mfr.isin(mfr))
]
.groupby(['origin', 'mpg'])[yaxis].mean()
.to_frame()
.reset_index()
.sort_values(by='mpg')
.reset_index(drop=True)
)
# Pipe to hvplot
ihvplot = ipipeline.hvplot(x='mpg', y=yaxis, by='origin', color=[
"#ff6f69", "#ffcc5c", "#88d8b0"], line_width=6, height=400)
# Layout using Template
template = pn.template.FastListTemplate(
title='Interactive DataFrame Dashboards with hvplot .interactive',
sidebar=[cylinders, 'Manufacturers', mfr, 'Y axis', yaxis],
main=[ihvplot.panel()],
accent_base_color="#88d8b0",
header_background="#88d8b0",
)
template.servable()
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