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import altair as alt |
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import gradio as gr |
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import numpy as np |
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import pandas as pd |
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from vega_datasets import data |
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def make_plot(plot_type): |
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if plot_type == "scatter_plot": |
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cars = data.cars() |
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return alt.Chart(cars).mark_point().encode( |
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x='Horsepower', |
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y='Miles_per_Gallon', |
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color='Origin', |
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) |
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elif plot_type == "heatmap": |
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x, y = np.meshgrid(range(-5, 5), range(-5, 5)) |
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z = x ** 2 + y ** 2 |
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source = pd.DataFrame({'x': x.ravel(), |
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'y': y.ravel(), |
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'z': z.ravel()}) |
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return alt.Chart(source).mark_rect().encode( |
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x='x:O', |
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y='y:O', |
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color='z:Q' |
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) |
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elif plot_type == "us_map": |
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states = alt.topo_feature(data.us_10m.url, 'states') |
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source = data.income.url |
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return alt.Chart(source).mark_geoshape().encode( |
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shape='geo:G', |
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color='pct:Q', |
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tooltip=['name:N', 'pct:Q'], |
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facet=alt.Facet('group:N', columns=2), |
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).transform_lookup( |
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lookup='id', |
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from_=alt.LookupData(data=states, key='id'), |
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as_='geo' |
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).properties( |
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width=300, |
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height=175, |
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).project( |
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type='albersUsa' |
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) |
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elif plot_type == "interactive_barplot": |
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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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plot = 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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return plot |
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elif plot_type == "radial": |
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source = pd.DataFrame({"values": [12, 23, 47, 6, 52, 19]}) |
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base = alt.Chart(source).encode( |
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theta=alt.Theta("values:Q", stack=True), |
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radius=alt.Radius("values", scale=alt.Scale(type="sqrt", zero=True, rangeMin=20)), |
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color="values:N", |
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) |
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c1 = base.mark_arc(innerRadius=20, stroke="#fff") |
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c2 = base.mark_text(radiusOffset=10).encode(text="values:Q") |
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return c1 + c2 |
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elif plot_type == "multiline": |
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source = data.stocks() |
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highlight = alt.selection(type='single', on='mouseover', |
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fields=['symbol'], nearest=True) |
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base = alt.Chart(source).encode( |
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x='date:T', |
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y='price:Q', |
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color='symbol:N' |
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) |
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points = base.mark_circle().encode( |
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opacity=alt.value(0) |
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).add_selection( |
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highlight |
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).properties( |
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width=600 |
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) |
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lines = base.mark_line().encode( |
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size=alt.condition(~highlight, alt.value(1), alt.value(3)) |
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) |
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return points + lines |
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with gr.Blocks() as demo: |
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button = gr.Radio(label="Plot type", |
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choices=['scatter_plot', 'heatmap', 'us_map', |
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'interactive_barplot', "radial", "multiline"], value='scatter_plot') |
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plot = gr.Plot(label="Plot") |
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button.change(make_plot, inputs=button, outputs=[plot]) |
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demo.load(make_plot, inputs=[button], outputs=[plot]) |
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if __name__ == "__main__": |
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demo.launch() |
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