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import gradio as gr
from vega_datasets import data
cars = data.cars()
iris = data.iris()
def scatter_plot_fn(dataset):
if dataset == "iris":
return gr.ScatterPlot(
value=iris,
x="petalWidth",
y="petalLength",
color="species",
title="Iris Dataset",
color_legend_title="Species",
x_title="Petal Width",
y_title="Petal Length",
tooltip=["petalWidth", "petalLength", "species"],
caption="",
)
else:
return gr.ScatterPlot(
value=cars,
x="Horsepower",
y="Miles_per_Gallon",
color="Origin",
tooltip="Name",
title="Car Data",
y_title="Miles per Gallon",
color_legend_title="Origin of Car",
caption="MPG vs Horsepower of various cars",
)
with gr.Blocks() as scatter_plot:
with gr.Row():
with gr.Column():
dataset = gr.Dropdown(choices=["cars", "iris"], value="cars")
with gr.Column():
plot = gr.ScatterPlot(show_label=False)
dataset.change(scatter_plot_fn, inputs=dataset, outputs=plot)
scatter_plot.load(fn=scatter_plot_fn, inputs=dataset, outputs=plot)
if __name__ == "__main__":
scatter_plot.launch()
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