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Browse files- requirements.txt +2 -2
- run.ipynb +1 -1
- run.py +1 -1
requirements.txt
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gradio-client @ git+https://github.com/gradio-app/gradio@
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https://gradio-pypi-previews.s3.amazonaws.com/
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gradio-client @ git+https://github.com/gradio-app/gradio@d68c663fc9fffed4840fd74bed940fba3e2bc174#subdirectory=client/python
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https://gradio-pypi-previews.s3.amazonaws.com/d68c663fc9fffed4840fd74bed940fba3e2bc174/gradio-5.42.0-py3-none-any.whl
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run.ipynb
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: plot_guide_aggregate_temporal"]}, {"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_aggregate_temporal/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", " plot = gr.BarPlot(df, x=\"time\", y=\"price\", x_bin=\"10m\")\n", "\n", " bins = gr.Radio([\"10m\", \"30m\", \"1h\"], label=\"Bin Size\")\n", " bins.change(lambda bins: gr.BarPlot(x_bin=bins), bins, plot)\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_aggregate_temporal"]}, {"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_aggregate_temporal/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", " plot = gr.BarPlot(df, x=\"time\", y=\"price\", x_bin=\"10m\")\n", "\n", " bins = gr.Radio([\"10m\", \"30m\", \"1h\"], label=\"Bin Size\")\n", " bins.change(lambda bins: gr.BarPlot(x_bin=bins), bins, plot)\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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plot = gr.BarPlot(df, x="time", y="price", x_bin="10m")
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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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plot = gr.BarPlot(df, x="time", y="price", x_bin="10m")
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