From 73c40877c2267fb4c6dad472cd4244c067f6f14d Mon Sep 17 00:00:00 2001
From: Philip Chmielowiec <philipchmielowiec@gmail.com>
Date: Sun, 10 Dec 2023 11:55:37 -0800
Subject: [PATCH] a few more typos

---
 notebooks/03-uxarray-vis/03-polygons.ipynb    |  6 +++---
 notebooks/03-uxarray-vis/06-performance.ipynb | 10 ++++++++++
 2 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/notebooks/03-uxarray-vis/03-polygons.ipynb b/notebooks/03-uxarray-vis/03-polygons.ipynb
index 705d9348..e6a9ee6f 100644
--- a/notebooks/03-uxarray-vis/03-polygons.ipynb
+++ b/notebooks/03-uxarray-vis/03-polygons.ipynb
@@ -98,7 +98,7 @@
    "cell_type": "markdown",
    "source": [
     "## Conversion Methods\n",
-    "UXarray represents Unstructured Grids through a set of coordinate and connectivity variables (i.e. `node_lon`, `node_lat`, `face_node_connectivity`, etc.). These variables can be manipulated to obtain our Polygons for visualuzation"
+    "UXarray represents Unstructured Grids through a set of coordinate and connectivity variables (i.e. `node_lon`, `node_lat`, `face_node_connectivity`, etc.). These variables need to be manipulated to obtain geometries and data structures that are compatible with visualuzation libraries (i.e. HoloViews, Datashader, Matplotlib, etc.)"
    ],
    "metadata": {
     "collapsed": false
@@ -109,7 +109,7 @@
    "source": [
     "### Representation as a `GeoDataFrame`\n",
     "\n",
-    "Polygons are stored in a SpatialPandas `GeoDataFrame`, which is the expected data structured by the HoloViz stack of packages for visualizing polygons.\n",
+    "Each face is converted into a Polygon and stored within a SpatialPandas `GeoDataFrame`, which is the expected data structured by the HoloViz stack of packages for visualizing polygons.\n",
     "\n"
    ],
    "metadata": {
@@ -161,7 +161,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "If a data variable is not face-centered, it can be manipulated to get it to map to faces. For node-centered data, as is the case with our Geoflow dataset, we can perform a nodal-average operation, which takes the average all the nodes that saddle a face and use that value to shade the polygon.\n",
+    "If a data variable is not face-centered, it can be manipulated to become face-centered. For node-centered data, as is the case with our Geoflow dataset, we can perform a nodal-average operation, which takes the average all the nodes that surround a face and use that value to shade the polygon.\n",
     "\n",
     "Here we can also see that we need to index the `time` and `meshLayers` dimensions to obtain our 1D slice of data."
    ],
diff --git a/notebooks/03-uxarray-vis/06-performance.ipynb b/notebooks/03-uxarray-vis/06-performance.ipynb
index f976aaca..5a84f1e1 100644
--- a/notebooks/03-uxarray-vis/06-performance.ipynb
+++ b/notebooks/03-uxarray-vis/06-performance.ipynb
@@ -305,6 +305,16 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "is_executing": true
+   }
+  },
   {
    "cell_type": "markdown",
    "source": [