diff --git a/book/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.ipynb b/book/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.ipynb
index 133532d..8b79a50 100644
--- a/book/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.ipynb
+++ b/book/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.ipynb
@@ -39,7 +39,7 @@
    "source": [
     "We will set up our computing environment with library imports and utility functions\n",
     "\n",
-    "Tip: If you need to import a library that is not pre-installed, use `%pip install <package-name>` alone within a Jupyter notebook cell to install it for this instance of CryoCloud (the pip installation will not presist between logins. All of the libraries we intend to use are pre-installed so we can skip this step. "
+    "Tip: If you need to import a library that is not pre-installed, use `%pip install <package-name>` alone within a Jupyter notebook cell to install it for this instance of CryoCloud (the pip installation will not presist between logins). "
    ]
   },
   {
@@ -53,8 +53,7 @@
    "outputs": [],
    "source": [
     "# Needed for pandas read_excel\n",
-    "%pip install openpyxl\n",
-    "%pip install ~/icepyx"
+    "%pip install openpyxl"
    ]
   },
   {
@@ -182,7 +181,7 @@
     "user_expressions": []
    },
    "source": [
-    "However, since this data has a direct download URL, so we can read the data directly into CryoCloud skipping the download and upload steps, like so: "
+    "However, this data has a direct download URL, so we can read the data directly into our notebook, skipping the download and upload steps: "
    ]
   },
   {
@@ -195,41 +194,6 @@
     "## Open data directly via URL"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "047bbc78-a049-4055-8002-425d6881b70a",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Read in spreadsheet using pandas read_excel\n",
-    "use_cols = ['Name / Location', 'Lat. oN', 'Lon. oE', 'Lake Type', 'References']\n",
-    "import_rows = np.arange(0,65)\n",
-    "# You may add a path/to/file if you'd like to try reading spreadsheet from where you saved it in a data directory \n",
-    "df = pd.read_excel('43017_2021_246_MOESM1_ESM.xlsx', 'Greenland', usecols=use_cols, skiprows = lambda x: x not in import_rows)\n",
-    "\n",
-    "# View pandas dataset head (first 5 rows)\n",
-    "df.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0b979f8c-8bb5-446c-8511-283025ff945d",
-   "metadata": {},
-   "source": [
-    "However, since this data has a direct download URL, so we can read the data directly into CryoCloud skipping the download and upload steps, like so: "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fff870cc-3b5e-42df-8ce0-a3c256ad4ffd",
-   "metadata": {},
-   "source": [
-    "## Open data directly via URL"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 4,
@@ -1165,8 +1129,7 @@
    },
    "outputs": [],
    "source": [
-    "# Import earthaccess Library and view version\n",
-    "import earthaccess\n",
+    "# view version\n",
     "print(f\"Using earthaccess v{earthaccess.__version__}\")"
    ]
   },