ITables NCL Index

environment.yml

@@ -23,6 +23,7 @@ dependencies:
   - jupyter_client
 
   # Infrastructure
+  - itables
   - myst-nb
   - nbsphinx
   - pre-commit

ncl/ncl_index/ncl-index-table-demo.csv

@@ -0,0 +1,4 @@
+NCL Function,Description,Python Equivalent,Notes
+<a href="https://www.ncl.ucar.edu/Document/Functions/Built-in/sin.shtml"><code>sin()</code></a>, Computes the sine of numeric types, <code>math.sin()</code> or <code>numpy.sin()</code>, <a href="../ncl_entries/trigonometry.ipynb#sin">example notebook</a>
+<a href="https://www.ncl.ucar.edu/Document/Functions/Built-in/cos.shtml"><code>cos()</code></a>, Computes the cosine of numeric types, <code>math.cos()</code> or <code>numpy.cos()</code>, <a href="../ncl_entries/trigonometry.ipynb#cos">example notebook</a>
+<a href="https://www.ncl.ucar.edu/Document/Functions/Built-in/tan.shtml"><code>tan()</code></a>, Computes the tangent of numeric types,  <code>math.tan()</code> or <code>numpy.tan()</code>, <a href="../ncl_entries/trigonometry.ipynb#tan">example notebook</a>

ncl/ncl_index/ncl_index.ipynb

@@ -0,0 +1,97 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4a6382b1-e561-4402-ae72-58b2b96fa630",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# NCL Index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "36aab5eb-87cf-46da-9a2f-68eda52f4154",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "remove-input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "import itables\n",
+    "import pandas as pd\n",
+    "\n",
+    "itables.init_notebook_mode(connected=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0eec630a-1d88-4ef8-bb52-883fc6515371",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "remove-input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv('ncl-index-table-demo.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b409366c-3989-4b13-9316-08d1077a067c",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "remove-input",
+     "full-width"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "itables.show(df, allow_html=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}