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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() | |