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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: dataframe_events"]}, {"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", "\n", "def update_dataframe():\n", " regular_df = pd.DataFrame(np.random.randint(1, 10, size=(5, 5)), columns=pd.Index([str(i) for i in range(5)]))\n", " wide_df = pd.DataFrame([\n", " [5, 22, 91, 17, 73, 38, 84, 46, 65, 10, 155, 122, 11, 144, 133],\n", " [81, 42, 13, 97, 33, 77, 59, 100, 29, 61, 213, 195, 142, 118, 127],\n", " [37, 71, 63, 102, 28, 94, 19, 55, 88, 44, 116, 139, 122, 150, 147],\n", " [104, 52, 49, 26, 83, 67, 31, 92, 79, 18, 241, 115, 159, 123, 137],\n", " [16, 95, 74, 68, 43, 101, 27, 85, 39, 57, 129, 148, 132, 111, 156]\n", " ], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", " return regular_df, wide_df\n", "\n", "def clear_dataframes():\n", " regular_empty_df = pd.DataFrame([], columns=pd.Index([str(i) for i in range(5)]))\n", " wide_empty_df = pd.DataFrame([], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", " return regular_empty_df, wide_empty_df\n", "\n", "def increment_select_counter(evt: gr.SelectData, count):\n", " count_val = 1 if count is None else count + 1\n", " return count_val, evt.index, evt.value\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " with gr.Column(scale=1):\n", " initial_regular_df = pd.DataFrame(np.zeros((5, 5), dtype=int), columns=pd.Index([str(i) for i in range(5)]))\n", "\n", " df = gr.Dataframe(\n", " value=initial_regular_df,\n", " interactive=True,\n", " label=\"Interactive Dataframe\",\n", " show_label=True,\n", " elem_id=\"dataframe\",\n", " show_search=\"filter\",\n", " show_copy_button=True,\n", " show_row_numbers=True,\n", " static_columns=[4]\n", " )\n", "\n", " with gr.Column(scale=1):\n", " initial_wide_df = pd.DataFrame(np.zeros((5, 15), dtype=int), columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "\n", " df_view = gr.Dataframe(\n", " value=initial_wide_df,\n", " interactive=False,\n", " label=\"Non-Interactive View (Scroll Horizontally)\",\n", " show_label=True,\n", " show_search=\"search\",\n", " elem_id=\"non-interactive-dataframe\",\n", " show_copy_button=True,\n", " show_row_numbers=True,\n", " show_fullscreen_button=True,\n", " )\n", "\n", " tall_df_value = [\n", " [\"DeepSeek Coder\", 79.3, True],\n", " [\"Llama 3.3\", 68.9, True],\n", " [\"Qwen 2.5\", 61.9, True],\n", " [\"Gemma 2\", 59.5, False],\n", " [\"GPT 2\", 18.3, False],\n", " ]\n", "\n", " def get_display_value(values):\n", " display_values = []\n", " medals = [\"\ud83e\udd47\", \"\ud83e\udd48\", \"\ud83e\udd49\"]\n", " for i, row in enumerate(values):\n", " if i < 3:\n", " display_values.append([f\"{medals[i]} {row[0]}\", row[1]])\n", " else:\n", " display_values.append([row[0], row[1]])\n", " return display_values\n", "\n", " display_value = get_display_value(tall_df_value)\n", "\n", " tall_df_value = {\n", " \"data\": tall_df_value,\n", " \"headers\": [\"Model\", \"% Correct (LeetCode Hard)\", \"Is Open Source\"],\n", " \"metadata\": {\n", " \"display_value\": display_value\n", " }\n", " }\n", "\n", " with gr.Row():\n", " with gr.Column():\n", " df_tall = gr.Dataframe(\n", " value=tall_df_value,\n", " interactive=False,\n", " label=\"Tall Dataframe (Scroll Vertically)\",\n", " datatype=[\"str\", \"number\", \"bool\"],\n", " max_height=200,\n", " show_label=True,\n", " elem_id=\"dataframe_tall\",\n", " show_copy_button=True,\n", " show_row_numbers=True,\n", " show_search=\"search\",\n", " )\n", "\n", " df_tall_selected_cell_index = gr.Textbox(\n", " label=\"Tall dataframe selected cell index\", elem_id=\"tall_selected_cell_index\"\n", " )\n", " df_tall_selected_cell_value = gr.Textbox(\n", " label=\"Tall dataframe selected cell value\", elem_id=\"tall_selected_cell_value\"\n", " )\n", "\n", " with gr.Row():\n", " with gr.Column():\n", " update_btn = gr.Button(\"Update dataframe\", elem_id=\"update_btn\")\n", " clear_btn = gr.Button(\"Clear dataframe\", elem_id=\"clear_btn\")\n", "\n", " with gr.Row():\n", " change_events = gr.Number(\n", " value=0, label=\"Change events\", elem_id=\"change_events\"\n", " )\n", " input_events = gr.Number(value=0, label=\"Input events\", elem_id=\"input_events\")\n", " select_events = gr.Number(\n", " value=0, label=\"Select events\", elem_id=\"select_events\"\n", " )\n", "\n", " with gr.Row():\n", " selected_cell_index = gr.Textbox(\n", " label=\"Selected cell index\", elem_id=\"selected_cell_index\"\n", " )\n", " selected_cell_value = gr.Textbox(\n", " label=\"Selected cell value\", elem_id=\"selected_cell_value\"\n", " )\n", "\n", " update_btn.click(fn=update_dataframe, outputs=[df, df_view])\n", " clear_btn.click(fn=clear_dataframes, outputs=[df, df_view, df_tall])\n", " df.change(fn=lambda x: x + 1, inputs=[change_events], outputs=[change_events])\n", " df.input(fn=lambda x: x + 1, inputs=[input_events], outputs=[input_events])\n", " df.select(\n", " fn=increment_select_counter,\n", " inputs=[select_events],\n", " outputs=[select_events, selected_cell_index, selected_cell_value],\n", " )\n", "\n", " df_tall.select(\n", " fn=increment_select_counter,\n", " inputs=[select_events],\n", " outputs=[select_events, df_tall_selected_cell_index, df_tall_selected_cell_value],\n", " )\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} |