cleanup

notebooks/wp5/lake_water_temperature_outlier_detection.ipynb

@@ -50,7 +50,7 @@
    "source": [
     "# Time\n",
     "start = \"1997-01\"\n",
-    "stop = \"1997-02\"\n",
+    "stop = \"2000-01\"\n",
     "\n",
     "# Region\n",
     "lon_slice = slice(28, 41)\n",
@@ -151,20 +151,6 @@
     "da = ds[varname].compute()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "328f352f",
-   "metadata": {
-    "editable": true,
-    "slideshow": {
-     "slide_type": ""
-    },
-    "tags": []
-   },
-   "source": [
-    "## Extract lake IDs to plot a map of the region"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -173,8 +159,10 @@
    "outputs": [],
    "source": [
     "# We use one of the request previously cached\n",
-    "single_request = requests[0]\n",
-    "single_request[\"month\"] = single_request[\"month\"][0]\n",
+    "single_request = {\n",
+    "    k: v if isinstance(v, str) or k not in chunks else v[0]\n",
+    "    for k, v in requests[0].items()\n",
+    "}\n",
     "da_lakeid = download.download_and_transform(\n",
     "    collection_id,\n",
     "    single_request,\n",
@@ -255,7 +243,10 @@
     "plt.show()\n",
     "\n",
     "# Print statistics\n",
-    "boxplot_stats = {}\n",
+    "boxplot_stats = {\n",
+    "    lakeid: matplotlib.cbook.boxplot_stats(df_lakeid.dropna().values.squeeze())\n",
+    "    for lakeid, df_lakeid in df.groupby(\"lakeid\")\n",
+    "}\n",
     "for lakeid, df_lakeid in df.groupby(\"lakeid\"):\n",
     "    values = df_lakeid.dropna().values.squeeze()\n",
     "    (boxplot_stats[lakeid],) = matplotlib.cbook.boxplot_stats(values)\n",