import altair as alt import gradio as gr import numpy as np import pandas as pd from vega_datasets import data def make_plot(plot_type): if plot_type == "interactive_barplot": source = data.movies.url pts = alt.selection(type="single", encodings=['x']) rect = alt.Chart(data.movies.url).mark_rect().encode( alt.X('IMDB_Rating:Q', bin=True), alt.Y('Rotten_Tomatoes_Rating:Q', bin=True), alt.Color('count()', scale=alt.Scale(scheme='greenblue'), legend=alt.Legend(title='Total Records') ) ) circ = rect.mark_point().encode( alt.ColorValue('grey'), alt.Size('count()', legend=alt.Legend(title='Records in Selection') ) ).transform_filter( pts ) bar = alt.Chart(source).mark_bar().encode( x='Major_Genre:N', y='count()', color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey")) ).properties( width=550, height=200 ).add_selection(pts) plot = alt.vconcat( rect + circ, bar ).resolve_legend( color="independent", size="independent" ) return plot elif plot_type == "multiline": source = data.stocks() highlight = alt.selection(type='single', on='mouseover', fields=['symbol'], nearest=True) base = alt.Chart(source).encode( x='date:T', y='price:Q', color='symbol:N' ) points = base.mark_circle().encode( opacity=alt.value(0) ).add_selection( highlight ).properties( width=600 ) lines = base.mark_line().encode( size=alt.condition(~highlight, alt.value(1), alt.value(3)) ) return points + lines with gr.Blocks() as demo: button = gr.Radio(label="Plot type", choices=['interactive_barplot', "multiline"], value='interactive_barplot') plot = gr.Plot(label="Plot") button.change(make_plot, inputs=button, outputs=[plot]) demo.load(make_plot, inputs=[button], outputs=[plot]) if __name__ == "__main__": demo.launch()