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panel_kmeans.html
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panel_kmeans.html
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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="apple-mobile-web-app-capable" content="yes" />
<meta name="apple-mobile-web-app-status-bar-style" content="default" />
<meta name="theme-color" content="#000000" />
<meta name="name" content="PyScript/Panel KMeans Demo" />
<title>Pyscript/Panel KMeans Demo</title>
<link rel="icon" type="image/x-icon" href="./favicon.png" />
<link
rel="stylesheet"
href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css"
type="text/css"
/>
<link
rel="stylesheet"
href="https://unpkg.com/@holoviz/panel@0.13.1/dist/css/widgets.css"
type="text/css"
/>
<link
rel="stylesheet"
href="https://unpkg.com/@holoviz/panel@0.13.1/dist/css/markdown.css"
type="text/css"
/>
<script
type="text/javascript"
src="https://cdn.jsdelivr.net/npm/vega@5"
></script>
<script
type="text/javascript"
src="https://cdn.jsdelivr.net/npm/vega-lite@5"
></script>
<script
type="text/javascript"
src="https://cdn.jsdelivr.net/npm/vega-embed@6"
></script>
<script
type="text/javascript"
src="https://unpkg.com/tabulator-tables@4.9.3/dist/js/tabulator.js"
></script>
<script
type="text/javascript"
src="https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.js"
></script>
<script
type="text/javascript"
src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js"
></script>
<script
type="text/javascript"
src="https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js"
></script>
<script
type="text/javascript"
src="https://unpkg.com/@holoviz/panel@0.13.1/dist/panel.min.js"
></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
<link
rel="stylesheet"
href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/css/bootstrap.min.css"
/>
<link
rel="stylesheet"
href="https://unpkg.com/@holoviz/panel@0.13.1/dist/bundled/bootstraptemplate/bootstrap.css"
/>
<link
rel="stylesheet"
href="https://unpkg.com/@holoviz/panel@0.13.1/dist/bundled/defaulttheme/default.css"
/>
<style>
#sidebar {
width: 350px;
}
</style>
<script src="https://cdn.jsdelivr.net/npm/jquery@3.5.1/dist/jquery.slim.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/js/bootstrap.bundle.min.js"></script>
<link
rel="stylesheet"
href="https://pyscript.net/latest/pyscript.css"
/>
<script defer src="https://pyscript.net/latest/pyscript.js"></script>
<link rel="stylesheet" href="./assets/css/examples.css" />
</head>
<body>
<nav class="navbar" style="background-color: #000000">
<div class="app-header">
<a href="/">
<img src="./logo.png" class="logo" />
</a>
<a class="title" href="" style="color: #f0ab3c"
>Panel KMeans Clustering Demo</a
>
</div>
</nav>
<section class="pyscript">
<div class="row overflow-hidden" id="content">
<div class="sidenav" id="sidebar">
<ul class="nav flex-column">
<div class="bk-root" id="x-widget"></div>
<div class="bk-root" id="y-widget"></div>
<div class="bk-root" id="n-widget"></div>
</ul>
</div>
<div class="col mh-100 float-left" id="main">
<div class="bk-root" id="intro"></div>
<div class="bk-root" id="cluster-plot"></div>
<div class="bk-root" id="table"></div>
</div>
</div>
<py-tutor>
<py-config>
packages = [
"https://cdn.holoviz.org/panel/0.14.3/dist/wheels/bokeh-2.4.3-py3-none-any.whl",
"altair",
"numpy",
"pandas",
"scikit-learn",
"panel==0.13.1"
]
plugins = [
"https://pyscript.net/latest/plugins/python/py_tutor.py"
]
</py-config>
<py-script>
import altair as alt
import panel as pn
import pandas as pd
from sklearn.cluster import KMeans
from pyodide.http import open_url
pn.config.sizing_mode = 'stretch_width'
url = 'https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv'
penguins = pd.read_csv(open_url(url)).dropna()
cols = list(penguins.columns)[2:6]
x = pn.widgets.Select(name='x', options=cols, value='bill_depth_mm').servable(target='x-widget')
y = pn.widgets.Select(name='y', options=cols, value='bill_length_mm').servable(target='y-widget')
n_clusters = pn.widgets.IntSlider(name='n_clusters', start=1, end=5, value=3).servable(target='n-widget')
brush = alt.selection_interval(name='brush') # selection of type "interval"
def get_clusters(n_clusters):
kmeans = KMeans(n_clusters=n_clusters)
est = kmeans.fit(penguins[cols].values)
df = penguins.copy()
df['labels'] = est.labels_.astype('str')
return df
def get_chart(x, y, df):
centers = df.groupby('labels').mean()
return (
alt.Chart(df)
.mark_point(size=100)
.encode(
x=alt.X(x, scale=alt.Scale(zero=False)),
y=alt.Y(y, scale=alt.Scale(zero=False)),
shape='labels',
color='species'
).add_selection(brush).properties(width=800) +
alt.Chart(centers)
.mark_point(size=250, shape='cross', color='black')
.encode(x=x+':Q', y=y+':Q')
)
intro = pn.pane.Markdown("""
This app provides an example of **building a simple dashboard using
Panel**.\n\nIt demonstrates how to take the output of **k-means
clustering on the Penguins dataset** using scikit-learn,
parameterizing the number of clusters and the variables to
plot.\n\nThe plot and the table are linked, i.e. selecting on the plot
will filter the data in the table.\n\n The **`x` marks the center** of
the cluster.
""").servable(target='intro')
chart = pn.pane.Vega().servable(target='cluster-plot')
table = pn.widgets.Tabulator(pagination='remote', page_size=10).servable(target='table')
def update_table(event=None):
table.value = get_clusters(n_clusters.value)
n_clusters.param.watch(update_table, 'value')
@pn.depends(x, y, n_clusters, watch=True)
def update_chart(*events):
chart.object = get_chart(x.value, y.value, table.value)
chart.selection.param.watch(update_filters, 'brush')
def update_filters(event=None):
filters = []
for k, v in (getattr(event, 'new') or {}).items():
filters.append(dict(field=k, type='>=', value=v[0]))
filters.append(dict(field=k, type='<=', value=v[1]))
table.filters = filters
update_table()
update_chart()
</py-script>
</py-tutor>
</section>
<script>
$(document).ready(function () {
$("#sidebarCollapse").on("click", function () {
$("#sidebar").toggleClass("active");
$(this).toggleClass("active");
var interval = setInterval(function () {
window.dispatchEvent(new Event("resize"));
}, 10);
setTimeout(function () {
clearInterval(interval);
}, 210);
});
});
</script>
</body>
</html>