Add Dataset examples to rechunk_no_shuffle notebook (#1069)

Author: brendancol

examples/user_guide/36_Rechunk_No_Shuffle.ipynb

@@ -147,6 +147,25 @@
     "assert result is numpy_dem\n",
     "print('Numpy passthrough: OK')"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "source": "## Dataset support\n\n`rechunk_no_shuffle` also accepts `xr.Dataset`. Each dask-backed variable\nis rechunked independently; numpy-backed variables pass through unchanged.",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "source": "ds = xr.Dataset({\n    'elevation': dem,\n    'slope': xr.DataArray(\n        da.from_array(np.random.rand(4096, 4096).astype(np.float32), chunks=256),\n        dims=['y', 'x'],\n    ),\n    'mask': xr.DataArray(np.ones((4096, 4096), dtype=np.uint8), dims=['y', 'x']),\n})\n\nds_big = rechunk_no_shuffle(ds, target_mb=64)\n\nfor name in ds.data_vars:\n    if hasattr(ds[name].data, 'dask'):\n        print(f'{name}: {ds[name].chunks[0][0]} -> {ds_big[name].chunks[0][0]}')\n    else:\n        print(f'{name}: numpy (unchanged)')",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
+  },
+  {
+   "cell_type": "code",
+   "source": "# Works on the Dataset accessor too\nds_big_acc = ds.xrs.rechunk_no_shuffle(target_mb=64)\nassert ds_big['elevation'].chunks == ds_big_acc['elevation'].chunks\nprint('Dataset accessor: OK')",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
   }
  ],
  "metadata": {
@@ -162,4 +181,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}