run.ipynb

{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: scatterplot_component"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio vega_datasets"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from vega_datasets import data\n", "\n", "cars = data.cars()\n", "\n", "css = \"footer {display: none !important;} .gradio-container {min-height: 0px !important;}\"\n", "\n", "with gr.Blocks(css=css) as demo:\n", "    gr.ScatterPlot(show_label=False,\n", "                   value=cars,\n", "                   x=\"Horsepower\",\n", "                   y=\"Miles_per_Gallon\",\n", "                   color=\"Origin\",\n", "                   tooltip=\"Name\",\n", "                   title=\"Car Data\",\n", "                   y_title=\"Miles per Gallon\",\n", "                   color_legend_title=\"Origin of Car\").style(container=False)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}