Add the ADF comparison table to notebook

ADF stores the data for its comparison table in a CSV file, so we can import
pandas and then use display(HTML(df.to_html())) to get it rendered properly in
the notebook.

Also cleaned up the hist_str for time series in external_diag_packages

examples/external_diag_packages/config.yml

@@ -58,7 +58,7 @@ timeseries:
   atm:
     vars: ['PSL']
     derive_vars: []
-    hist_str: 'h0a'
+    hist_str: 'cam.h0a'
     start_years: [1,1]
     end_years: [100,100]
     level: 'lev'

nblibrary/atm/link_to_ADF.ipynb

@@ -36,8 +36,10 @@
    "outputs": [],
    "source": [
     "import os\n",
+    "\n",
     "from IPython.core.display import HTML, Image\n",
-    "from IPython.display import display"
+    "from IPython.display import display\n",
+    "import pandas as pd"
    ]
   },
   {
@@ -144,7 +146,29 @@
    "metadata": {},
    "source": [
     "## Key Metrics from ADF\n",
-    "These will eventually be put in the key_metrics example, but are a proof of concept of including individual plots from ADF directly linked in the JupyterBook."
+    "\n",
+    "Some important things to look at from ADF include a comparison table and a few maps:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5b02451-98ad-4089-b184-75391a262db3",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "hide-input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "comparison_table = os.path.join(adf_root, \"amwg_table_comp.csv\")\n",
+    "if os.path.isfile(comparison_table):\n",
+    "    table = pd.read_csv(comparison_table)\n",
+    "    display(HTML(table.to_html(index=False)))"
    ]
   },
   {