{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: bar_plot_demo"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio pandas "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import pandas as pd\n", "from random import randint, random\n", "import gradio as gr\n", "\n", "\n", "temp_sensor_data = pd.DataFrame(\n", "    {\n", "        \"time\": pd.date_range(\"2021-01-01\", end=\"2021-01-05\", periods=200),\n", "        \"temperature\": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],\n", "        \"humidity\": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],\n", "        \"location\": [\"indoor\", \"outdoor\"] * 100,\n", "    }\n", ")\n", "\n", "food_rating_data = pd.DataFrame(\n", "    {\n", "        \"cuisine\": [[\"Italian\", \"Mexican\", \"Chinese\"][i % 3] for i in range(100)],\n", "        \"rating\": [random() * 4 + 0.5 * (i % 3) for i in range(100)],\n", "        \"price\": [randint(10, 50) + 4 * (i % 3) for i in range(100)],\n", "        \"wait\": [random() for i in range(100)],\n", "    }\n", ")\n", "\n", "with gr.Blocks() as bar_plots:\n", "    with gr.Row():\n", "        start = gr.DateTime(\"2021-01-01 00:00:00\", label=\"Start\")\n", "        end = gr.DateTime(\"2021-01-05 00:00:00\", label=\"End\")\n", "        apply_btn = gr.Button(\"Apply\", scale=0)\n", "    with gr.Row():\n", "        group_by = gr.Radio([\"None\", \"30m\", \"1h\", \"4h\", \"1d\"], value=\"None\", label=\"Group by\")\n", "        aggregate = gr.Radio([\"sum\", \"mean\", \"median\", \"min\", \"max\"], value=\"sum\", label=\"Aggregation\")\n", "\n", "    temp_by_time = gr.BarPlot(\n", "        temp_sensor_data,\n", "        x=\"time\",\n", "        y=\"temperature\",\n", "    )\n", "    temp_by_time_location = gr.BarPlot(\n", "        temp_sensor_data,\n", "        x=\"time\",\n", "        y=\"temperature\",\n", "        color=\"location\",\n", "    )\n", "\n", "    time_graphs = [temp_by_time, temp_by_time_location]\n", "    group_by.change(\n", "        lambda group: [gr.BarPlot(x_bin=None if group == \"None\" else group)] * len(time_graphs),\n", "        group_by,\n", "        time_graphs\n", "    )\n", "    aggregate.change(\n", "        lambda aggregate: [gr.BarPlot(y_aggregate=aggregate)] * len(time_graphs),\n", "        aggregate,\n", "        time_graphs\n", "    )\n", "\n", "    def rescale(select: gr.SelectData):\n", "        return select.index\n", "    rescale_evt = gr.on([plot.select for plot in time_graphs], rescale, None, [start, end])\n", "\n", "    for trigger in [apply_btn.click, rescale_evt.then]:\n", "        trigger(\n", "            lambda start, end: [gr.BarPlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs\n", "        )\n", "\n", "    with gr.Row():\n", "        price_by_cuisine = gr.BarPlot(\n", "            food_rating_data,\n", "            x=\"cuisine\",\n", "            y=\"price\",\n", "        )\n", "        with gr.Column(scale=0):\n", "            gr.Button(\"Sort $ > $$$\").click(lambda: gr.BarPlot(sort=\"y\"), None, price_by_cuisine)\n", "            gr.Button(\"Sort $$$ > $\").click(lambda: gr.BarPlot(sort=\"-y\"), None, price_by_cuisine)\n", "            gr.Button(\"Sort A > Z\").click(lambda: gr.BarPlot(sort=[\"Chinese\", \"Italian\", \"Mexican\"]), None, price_by_cuisine)\n", "\n", "    with gr.Row():\n", "        price_by_rating = gr.BarPlot(\n", "            food_rating_data,\n", "            x=\"rating\",\n", "            y=\"price\",\n", "            x_bin=1,\n", "        )\n", "        price_by_rating_color = gr.BarPlot(\n", "            food_rating_data,\n", "            x=\"rating\",\n", "            y=\"price\",\n", "            color=\"cuisine\",\n", "            x_bin=1,\n", "            color_map={\"Italian\": \"red\", \"Mexican\": \"green\", \"Chinese\": \"blue\"},\n", "        )\n", "\n", "if __name__ == \"__main__\":\n", "    bar_plots.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}