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pyscript-python-html/pyscriptjs/examples/panel_kmeans.html
2022-04-19 15:09:46 -05:00

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HTML

<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Pyscript/Panel KMeans Demo</title>
<link rel="icon" href="https://unpkg.com/@holoviz/panel@0.13.0/dist/icons/favicon.ico" type="">
<meta name="name" content="PyScript/Panel KMeans Demo">
<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@0.13.0/dist/css/widgets.css" type="text/css" />
<link rel="stylesheet" href="https://unpkg.com/@holoviz/panel@0.13.0/dist/css/markdown.css" type="text/css" />
<link rel="stylesheet" href="https://unpkg.com/@holoviz/panel@0.13.0/dist/css/loading.css" type="text/css" />
<link rel="stylesheet" href="https://unpkg.com/@holoviz/panel@0.13.0/dist/css/dataframe.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-2.4.2.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.2.min.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.2.min.js"></script>
<script type="text/javascript" src="https://unpkg.com/@holoviz/panel@0.13.0/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@0.13.0/dist/bundled/bootstraptemplate/bootstrap.css">
<link rel="stylesheet" href="https://unpkg.com/@holoviz/panel@0.13.0/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="../build/pyscript.css" />
<script defer src="../build/pyscript.js"></script>
</head>
<body>
<py-env>
- bokeh
- numpy
- pandas
- scikit-learn
- panel
- altair
</py-env>
<div class="container-fluid d-flex flex-column vh-100 overflow-hidden" id="container">
<nav class="navbar navbar-expand-md navbar-dark sticky-top shadow" style="" id="header">
<button type="button" class="navbar-toggle collapsed" id="sidebarCollapse">
<span class="navbar-toggler-icon"></span>
</button>
<div class="app-header">
<a class="title" href="/" >&nbsp;Panel</a>
<span class="title">&nbsp;-</span>
<a class="title" href="" >&nbsp;Pyscript KMeans Clustering Demo</a>
</div>
</nav>
<div class="row overflow-hidden" id="content">
<div class="sidenav" id="sidebar">
<ul class="nav flex-column">
<div class="bk-root" id="x-widget" data-root-id="1021"></div>
<div class="bk-root" id="y-widget" data-root-id="1026"></div>
<div class="bk-root" id="n-widget" data-root-id="1031"></div>
</ul>
</div>
<div class="col mh-100 float-left" id="main">
<div class="bk-root" id="intro" data-root-id="1008"></div>
<div class="bk-root" id="cluster-plot" data-root-id="1009"></div>
<div class="bk-root" id="table" data-root-id="1009"></div>
</div>
</div>
</div>
<py-script>
import asyncio
from io import StringIO
from js import fetch
import altair as alt
import panel as pn
import pandas as pd
from panel.io.pyodide import show
from sklearn.cluster import KMeans
pn.config.sizing_mode = 'stretch_width'
data = await fetch('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv')
penguins = pd.read_csv(StringIO(await data.text())).dropna()
cols = list(penguins.columns)[2:6]
x = pn.widgets.Select(name='x', options=cols, value='bill_depth_mm')
y = pn.widgets.Select(name='y', options=cols, value='bill_length_mm')
n_clusters = pn.widgets.IntSlider(name='n_clusters', start=1, end=5, value=3)
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')
)
chart = pn.pane.Vega()
table = pn.widgets.Tabulator(pagination='remote', page_size=10)
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()
intro = """
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.
"""
await show(x, 'x-widget')
await show(y, 'y-widget')
await show(n_clusters, 'n-widget')
await show(intro, 'intro')
await show(chart, 'cluster-plot')
await show(table, 'table')
</py-script>
<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>