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README.md

@@ -1,12 +1,12 @@
+
 ---
-title: Plot Guide Interactive
-emoji: ⚡
-colorFrom: purple
-colorTo: gray
+title: plot_guide_interactive 
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
 sdk: gradio
 sdk_version: 4.39.0
-app_file: app.py
+app_file: run.py
 pinned: false
+hf_oauth: true
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

data.py

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+import pandas as pd
+import numpy as np
+import random
+
+df = pd.DataFrame({
+    'height': np.random.randint(50, 70, 25),
+    'weight': np.random.randint(120, 320, 25),
+    'age': np.random.randint(18, 65, 25),
+    'ethnicity': [random.choice(["white", "black", "asian"]) for _ in range(25)]
+})

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}

run.py

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+import gradio as gr
+from data import df
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        ethnicity = gr.Dropdown(["all", "white", "black", "asian"], value="all")
+        max_age = gr.Slider(18, 65, value=65)
+
+    def filtered_df(ethnic, age):
+        _df = df if ethnic == "all" else df[df["ethnicity"] == ethnic]
+        _df = _df[_df["age"] < age]
+        return _df
+
+    gr.ScatterPlot(filtered_df, inputs=[ethnicity, max_age], x="weight", y="height", title="Weight x Height")
+    gr.LinePlot(filtered_df, inputs=[ethnicity, max_age], x="age", y="height", title="Age x Height")
+
+if __name__ == "__main__":
+    demo.launch()