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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()
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