gradio/demo/plot_guide_temporal/run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: plot_guide_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": ["import gradio as gr\n", "import pandas as pd\n", "import numpy as np\n", "import random\n", "\n", "from datetime import datetime, timedelta\n", "now = datetime.now()\n", "\n", "df = pd.DataFrame({\n", "    'time': [now - timedelta(minutes=5*i) for i in range(25)],\n", "    'price': np.random.randint(100, 1000, 25),\n", "    'origin': [random.choice([\"DFW\", \"DAL\", \"HOU\"]) for _ in range(25)],\n", "    'destination': [random.choice([\"JFK\", \"LGA\", \"EWR\"]) for _ in range(25)],\n", "})\n", "\n", "with gr.Blocks() as demo:\n", "    gr.LinePlot(df, x=\"time\", y=\"price\")\n", "    gr.ScatterPlot(df, x=\"time\", y=\"price\", color=\"origin\")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}