Update plotting notebooks (xarray-contrib#107)

Author: dcherian

fundamentals/04.1_basic_plotting.ipynb

@@ -46,14 +46,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ds = xr.tutorial.open_dataset(\"air_temperature.nc\").rename({\"air\": \"Tair\"})\n",
-    "\n",
-    "# we will add a gradient field with appropriate attributes\n",
-    "ds[\"dTdx\"] = ds.Tair.differentiate(\"lon\") / 110e3 / np.cos(ds.lat * np.pi / 180)\n",
-    "ds[\"dTdy\"] = ds.Tair.differentiate(\"lat\") / 105e3\n",
-    "ds.dTdx.attrs = {\"long_name\": \"$∂T/∂x$\", \"units\": \"°C/m\"}\n",
-    "ds.dTdy.attrs = {\"long_name\": \"$∂T/∂y$\", \"units\": \"°C/m\"}\n",
-    "\n",
+    "ds = xr.tutorial.open_dataset(\"air_temperature_gradient\")\n",
     "ds"
    ]
   },

fundamentals/04.2_faceting.ipynb

@@ -40,14 +40,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ds = xr.tutorial.open_dataset(\"air_temperature.nc\").rename({\"air\": \"Tair\"})\n",
-    "\n",
-    "# we will add a gradient field with appropriate attributes\n",
-    "ds[\"dTdx\"] = ds.Tair.differentiate(\"lon\") / 110e3 / np.cos(ds.lat * np.pi / 180)\n",
-    "ds[\"dTdy\"] = ds.Tair.differentiate(\"lat\") / 105e3\n",
-    "ds.dTdx.attrs = {\"long_name\": \"$∂T/∂x$\", \"units\": \"°C/m\"}\n",
-    "ds.dTdy.attrs = {\"long_name\": \"$∂T/∂y$\", \"units\": \"°C/m\"}\n",
-    "\n",
+    "ds = xr.tutorial.open_dataset(\"air_temperature_gradient\")\n",
     "monthly_means = ds.groupby(\"time.month\").mean()\n",
     "# xarray's groupby reductions drop attributes. Let's assign them back so we get nice labels.\n",
     "monthly_means.Tair.attrs = ds.Tair.attrs"

fundamentals/04.3_geographic_plotting.ipynb

@@ -41,7 +41,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ds = xr.tutorial.open_dataset(\"air_temperature.nc\").rename({\"air\": \"Tair\"})\n",
+    "ds = xr.tutorial.open_dataset(\"air_temperature_gradient\")\n",
     "monthly_means = ds.groupby(\"time.month\").mean()\n",
     "# xarray's groupby reductions drop attributes. Let's assign them back so we get nice labels.\n",
     "monthly_means.Tair.attrs = ds.Tair.attrs"