PyCafe - Panel - A Dashbord with crossfiltering

app.py
requirements.txt
app.py
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import numpy as np
import pandas as pd
import panel as pn

import holoviews as hv
import hvplot.pandas # noqa

pn.extension(template='fast')

pn.state.template.logo = 'https://github.com/allisonhorst/palmerpenguins/raw/main/man/figures/logo.png'

welcome = "## Welcome and meet the Palmer penguins!"

penguins_art = pn.pane.PNG('https://raw.githubusercontent.com/allisonhorst/palmerpenguins/main/man/figures/palmerpenguins.png', height=160)

credit = "### Artwork by @allison_horst"

instructions = """
Use the box-select and lasso-select tools to select a subset of penguins
and reveal more information about the selected subgroup through the power
of cross-filtering.
"""

license = """
### License

Data are available by CC-0 license in accordance with the Palmer Station LTER Data Policy and the LTER Data Access Policy for Type I data."
"""

art = pn.Column(
    welcome, penguins_art, credit, instructions, license,
    sizing_mode='stretch_width'
).servable(area='sidebar')

penguins = pd.read_csv('https://datasets.holoviz.org/penguins/v1/penguins.csv')
penguins = penguins[~penguins.sex.isnull()].reset_index().sort_values('species')

ls = hv.link_selections.instance()

def count(selected):
    return f"## {len(selected)}/{len(penguins)} penguins selected"

selected = pn.pane.Markdown(
    pn.bind(count, ls.selection_param(penguins)),
    align='center', width=400, margin=(0, 100, 0, 0)
)

header = pn.Row(
    pn.layout.HSpacer(), selected,
    sizing_mode='stretch_width'
).servable(area='header')

colors = {
    'Adelie': '#1f77b4',
    'Gentoo': '#ff7f0e',
    'Chinstrap': '#2ca02c'
}

scatter = penguins.hvplot.points(
    'bill_length_mm', 'bill_depth_mm', c='species',
    cmap=colors, responsive=True, min_height=300
)

histogram = penguins.hvplot.hist(
    'body_mass_g', by='species', color=hv.dim('species').categorize(colors),
    legend=False, alpha=0.5, responsive=True, min_height=300
)

bars = penguins.hvplot.bar(
    'species', 'index', c='species', cmap=colors,
    responsive=True, min_height=300, ylabel=''
).aggregate(function=np.count_nonzero)

violin = penguins.hvplot.violin(
    'flipper_length_mm', by=['species', 'sex'], cmap='Category20',
    responsive=True, min_height=300, legend='bottom_right'
).opts(split='sex')

plots = pn.pane.HoloViews(
    ls(scatter.opts(show_legend=False) + bars + histogram + violin).opts(sizing_mode='stretch_both').cols(2)
).servable(title='Palmer Penguins')
Py.Cafe

penguin-crossfilter

A Dashbord with crossfiltering
