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Add altair, matplotlib and folium examples
This commit is contained in:
Philipp Rudiger
60
pyscriptjs/examples/altair.html
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60
pyscriptjs/examples/altair.html
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<html>
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<head>
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<title>Altair</title>
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<meta charset="utf-8">
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<link rel="stylesheet" href="../build/pyscript.css" />
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<script defer src="../build/pyscript.js"></script>
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<py-env>
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- altair
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- pandas
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- vega_datasets
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</py-env>
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</head>
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<body>
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<div id="altair" style="width: 100%; height: 100%"></div>
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<py-script output="altair">
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import altair as alt
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from vega_datasets import data
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source = data.movies.url
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pts = alt.selection(type="single", encodings=['x'])
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rect = alt.Chart(data.movies.url).mark_rect().encode(
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alt.X('IMDB_Rating:Q', bin=True),
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alt.Y('Rotten_Tomatoes_Rating:Q', bin=True),
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alt.Color('count()',
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scale=alt.Scale(scheme='greenblue'),
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legend=alt.Legend(title='Total Records')
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)
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)
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circ = rect.mark_point().encode(
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alt.ColorValue('grey'),
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alt.Size('count()',
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legend=alt.Legend(title='Records in Selection')
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)
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).transform_filter(
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pts
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)
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bar = alt.Chart(source).mark_bar().encode(
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x='Major_Genre:N',
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y='count()',
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color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey"))
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).properties(
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width=550,
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height=200
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).add_selection(pts)
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alt.vconcat(
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rect + circ,
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bar
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).resolve_legend(
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color="independent",
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size="independent"
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)
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</py-script>
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</body>
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</html>
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49
pyscriptjs/examples/folium.html
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49
pyscriptjs/examples/folium.html
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<html>
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<head>
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<title>Folium</title>
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<meta charset="utf-8">
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<link rel="stylesheet" href="../build/pyscript.css" />
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<script defer src="../build/pyscript.js"></script>
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<py-env>
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- folium
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- pandas
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</py-env>
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</head>
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<body>
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<div id="folium" style="width: 100%; height: 100%"></div>
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<py-script output="folium">
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import folium
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import json
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import pandas as pd
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from pyodide.http import open_url
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url = (
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"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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)
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state_geo = f"{url}/us-states.json"
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state_unemployment = f"{url}/US_Unemployment_Oct2012.csv"
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state_data = pd.read_csv(open_url(state_unemployment))
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geo_json = json.loads(open_url(state_geo).read())
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m = folium.Map(location=[48, -102], zoom_start=3)
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folium.Choropleth(
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geo_data=geo_json,
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name="choropleth",
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data=state_data,
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columns=["State", "Unemployment"],
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key_on="feature.id",
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fill_color="YlGn",
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fill_opacity=0.7,
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line_opacity=0.2,
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legend_name="Unemployment Rate (%)",
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).add_to(m)
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folium.LayerControl().add_to(m)
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m
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</py-script>
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</body>
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</html>
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50
pyscriptjs/examples/matplotlib.html
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pyscriptjs/examples/matplotlib.html
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<html>
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<head>
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<title>Matplotlib</title>
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<meta charset="utf-8">
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<link rel="stylesheet" href="../build/pyscript.css" />
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<script defer src="../build/pyscript.js"></script>
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<py-env>
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- matplotlib
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</py-env>
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</head>
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<body>
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<div id="mpl"></div>
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<py-script output="mpl">
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import matplotlib.pyplot as plt
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import matplotlib.tri as tri
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import numpy as np
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# First create the x and y coordinates of the points.
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n_angles = 36
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n_radii = 8
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min_radius = 0.25
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radii = np.linspace(min_radius, 0.95, n_radii)
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angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
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angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
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angles[:, 1::2] += np.pi / n_angles
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x = (radii * np.cos(angles)).flatten()
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y = (radii * np.sin(angles)).flatten()
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z = (np.cos(radii) * np.cos(3 * angles)).flatten()
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# Create the Triangulation; no triangles so Delaunay triangulation created.
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triang = tri.Triangulation(x, y)
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# Mask off unwanted triangles.
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triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1),
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y[triang.triangles].mean(axis=1))
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< min_radius)
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fig1, ax1 = plt.subplots()
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ax1.set_aspect('equal')
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tpc = ax1.tripcolor(triang, z, shading='flat')
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fig1.colorbar(tpc)
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ax1.set_title('tripcolor of Delaunay triangulation, flat shading')
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fig1
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</py-script>
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</body>
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</html>
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