Minor changes and typo fixes

intermediate/01-high-level-computation-patterns.ipynb

@@ -657,7 +657,7 @@
     ":class: dropdown\n",
     "\n",
     "```python\n",
-    "data.coarsen(lat=5, lon=5, boundary=\"trim\").reduce(np.mean).plot();\n",
+    "data.coarsen(lat=5, lon=5, boundary=\"trim\").reduce(np.ptp).plot();\n",
     "```\n",
     ":::\n",
     "::::"

intermediate/indexing/advanced-indexing.ipynb

@@ -154,7 +154,7 @@
     "\n",
     "ds = xr.tutorial.load_dataset(\"air_temperature\")\n",
     "da_air = ds.air\n",
-    "ds"
+    "da_air"
    ]
   },
   {
@@ -171,7 +171,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "👆 please notice how the output of the indexing example above resulted in an array of size `3x4`"
+    "👆 Please note that the output shape in the example above is `4x3` because the latitude indexer selects 4 rows, and the longitude indexer selects 3 columns."
    ]
   },
   {
@@ -239,7 +239,9 @@
     "To trigger vectorized indexing behavior, you will need to provide the selection dimensions with a new **shared** output dimension name. This means that the dimensions of both indexers must be the same, and the output will have the same dimension name as the indexers.\n",
     "```\n",
     "\n",
-    "Let's see how this works with an example. A researcher wants to find the nearest climate model grid cell to a collection of observation sites. She has the latitude and longitude of the observation sites as following:"
+    "Let's see how this works with an example:\n",
+    "\n",
+    "A researcher wants to find the nearest climate model grid cell to a collection of observation sites. They have the latitude and longitude of the observation sites as following:"
    ]
   },
   {
@@ -257,7 +259,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If the researcher use the lists to index the DataArray, they will get the orthogonal indexing behavior, which is not what they wants."
+    "If the researcher use the lists to index the DataArray, they will get the orthogonal indexing behavior, which is not what they want."
    ]
   },
   {