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README.md
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sdk: gradio
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sdk_version: 5.
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app_file: run.py
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pinned: false
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hf_oauth: true
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sdk: gradio
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sdk_version: 5.43.0
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app_file: run.py
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pinned: false
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hf_oauth: true
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run.ipynb
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: plot_guide_interactive"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/plot_guide_interactive/data.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from data import df\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " ethnicity = gr.Dropdown([\"all\", \"white\", \"black\", \"asian\"], value=\"all\")\n", " max_age = gr.Slider(18, 65, value=65)\n", "\n", " def filtered_df(ethnic, age):\n", " _df = df if ethnic == \"all\" else df[df[\"ethnicity\"] == ethnic]\n", " _df = _df[_df[\"age\"] < age]\n", " return _df\n", "\n", " gr.ScatterPlot(filtered_df, inputs=[ethnicity, max_age], x=\"weight\", y=\"height\", title=\"Weight x Height\")\n", " gr.LinePlot(filtered_df, inputs=[ethnicity, max_age], x=\"age\", y=\"height\", title=\"Age x Height\")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: plot_guide_interactive"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/plot_guide_interactive/data.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from data import df # type: ignore\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " ethnicity = gr.Dropdown([\"all\", \"white\", \"black\", \"asian\"], value=\"all\")\n", " max_age = gr.Slider(18, 65, value=65)\n", "\n", " def filtered_df(ethnic, age):\n", " _df = df if ethnic == \"all\" else df[df[\"ethnicity\"] == ethnic]\n", " _df = _df[_df[\"age\"] < age]\n", " return _df\n", "\n", " gr.ScatterPlot(filtered_df, inputs=[ethnicity, max_age], x=\"weight\", y=\"height\", title=\"Weight x Height\")\n", " gr.LinePlot(filtered_df, inputs=[ethnicity, max_age], x=\"age\", y=\"height\", title=\"Age x Height\")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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run.py
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import gradio as gr
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from data import df
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with gr.Blocks() as demo:
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with gr.Row():
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import gradio as gr
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from data import df # type: ignore
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with gr.Blocks() as demo:
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with gr.Row():
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