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run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: dataframe_datatype"]}, {"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", "\n", "def make_dataframe(n_periods):\n", "    rng = np.random.default_rng()\n", "    return pd.DataFrame({\"date_1\": pd.date_range(\"2021-01-01\", periods=n_periods),\n", "                         \"date_2\": pd.date_range(\"2022-02-15\", periods=n_periods).strftime('%B %d, %Y, %r'),\n", "                         \"number\": rng.random(n_periods).astype(np.float64),\n", "                         \"number_2\": rng.integers(0, 100, n_periods).astype(np.int32),\n", "                         \"bool\": [True] * n_periods,\n", "                         \"markdown\": [\"# Hello\"] * n_periods})\n", "\n", "\n", "demo = gr.Interface(make_dataframe,\n", "             gr.Number(precision=0),\n", "             gr.Dataframe(datatype=[\"date\", \"date\", \"number\", \"number\", \"bool\", \"markdown\"]))\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: dataframe_datatype"]}, {"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 make_dataframe(n_periods):\n", "    rng = np.random.default_rng()\n", "    return pd.DataFrame({\"date_1\": pd.date_range(\"2021-01-01\", periods=n_periods),\n", "                         \"date_2\": pd.date_range(\"2022-02-15\", periods=n_periods).strftime('%B %d, %Y, %r'),\n", "                         \"number\": rng.random(n_periods).astype(np.float64),\n", "                         \"number_2\": rng.integers(0, 100, n_periods).astype(np.int32),\n", "                         \"bool\": [True] * n_periods,\n", "                         \"markdown\": [\"# Hello\"] * n_periods})\n", "\n", "demo = gr.Interface(make_dataframe,\n", "             gr.Number(precision=0),\n", "             gr.Dataframe(datatype=[\"date\", \"date\", \"number\", \"number\", \"bool\", \"markdown\"]))\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -2,7 +2,6 @@ import gradio as gr
 import pandas as pd
 import numpy as np
 
-
 def make_dataframe(n_periods):
     rng = np.random.default_rng()
     return pd.DataFrame({"date_1": pd.date_range("2021-01-01", periods=n_periods),
@@ -12,11 +11,9 @@ def make_dataframe(n_periods):
                          "bool": [True] * n_periods,
                          "markdown": ["# Hello"] * n_periods})
 
-
 demo = gr.Interface(make_dataframe,
              gr.Number(precision=0),
              gr.Dataframe(datatype=["date", "date", "number", "number", "bool", "markdown"]))
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()