diff --git a/doc/source/plotting.ipynb b/doc/source/plotting.ipynb
index 3f9fb61..79479b4 100644
--- a/doc/source/plotting.ipynb
+++ b/doc/source/plotting.ipynb
@@ -17,7 +17,6 @@
    "source": [
     "import geodatasets\n",
     "import geopandas as gpd\n",
-    "import matplotlib.pyplot as plt\n",
     "import xarray as xr\n",
     "\n",
     "import xvec"
@@ -41,11 +40,11 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:200: SerializationWarning: variable 'z' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
+      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:204: SerializationWarning: variable 'z' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
       "  var = coder.decode(var, name=name)\n",
-      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:200: SerializationWarning: variable 'u' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
+      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:204: SerializationWarning: variable 'u' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
       "  var = coder.decode(var, name=name)\n",
-      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:200: SerializationWarning: variable 'v' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
+      "/Users/martin/dev/xvec/.pixi/envs/default/lib/python3.13/site-packages/xarray/conventions.py:204: SerializationWarning: variable 'v' has non-conforming '_FillValue' np.float64(nan) defined, dropping '_FillValue' entirely.\n",
       "  var = coder.decode(var, name=name)\n"
      ]
     },
@@ -422,35 +421,52 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 469kB\n",
-       "Dimensions:   (geometry: 3085, month: 2, level: 3)\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 494kB\n",
+       "Dimensions:     (level: 3, month: 2, geometry: 3085)\n",
        "Coordinates:\n",
-       "  * level     (level) int32 12B 200 500 850\n",
-       "  * month     (month) int32 8B 1 7\n",
-       "  * geometry  (geometry) object 25kB POLYGON ((-95.34258270263672 48.54670333...\n",
+       "  * level       (level) int32 12B 200 500 850\n",
+       "  * month       (month) int32 8B 1 7\n",
+       "  * geometry    (geometry) geometry 25kB POLYGON ((-95.34258270263672 48.5467...\n",
+       "    STATE_NAME  (geometry) object 25kB &#x27;Minnesota&#x27; &#x27;Washington&#x27; ... &#x27;Montana&#x27;\n",
        "Data variables:\n",
-       "    z         (geometry, month, level) float64 148kB 1.119e+05 ... 1.477e+04\n",
-       "    u         (geometry, month, level) float64 148kB 22.81 15.31 ... 12.0 0.9052\n",
-       "    v         (geometry, month, level) float64 148kB -10.04 -8.724 ... 0.4852\n",
+       "    z           (geometry, month, level) float64 148kB 1.116e+05 ... 1.477e+04\n",
+       "    u           (geometry, month, level) float64 148kB 22.19 14.94 ... 0.9052\n",
+       "    v           (geometry, month, level) float64 148kB -10.41 -8.828 ... 0.4852\n",
        "Indexes:\n",
        "    geometry  GeometryIndex (crs=EPSG:4326)\n",
        "Attributes:\n",
        "    Conventions:  CF-1.0\n",
-       "    Info:         Monthly ERA-Interim data. Downloaded and edited by fabien.m...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5dae6244-83e6-4ee9-8ee3-4aeb426cfaf3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5dae6244-83e6-4ee9-8ee3-4aeb426cfaf3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>geometry</span>: 3085</li><li><span class='xr-has-index'>month</span>: 2</li><li><span class='xr-has-index'>level</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f42fcbda-b3b0-475b-8f67-0a760164229b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f42fcbda-b3b0-475b-8f67-0a760164229b' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>200 500 850</div><input id='attrs-2e5e71df-6228-4eeb-bdfa-c33f5446866c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e5e71df-6228-4eeb-bdfa-c33f5446866c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42355054-282c-41f5-8c0e-37fe1d3f371d' class='xr-var-data-in' type='checkbox'><label for='data-42355054-282c-41f5-8c0e-37fe1d3f371d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([200, 500, 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 7</div><input id='attrs-518cefe0-4df5-4724-a24b-2df92d26e0a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-518cefe0-4df5-4724-a24b-2df92d26e0a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c801fafe-12ba-4e3d-99f3-c13cabc6febe' class='xr-var-data-in' type='checkbox'><label for='data-c801fafe-12ba-4e3d-99f3-c13cabc6febe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 7], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>geometry</span></div><div class='xr-var-dims'>(geometry)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((-95.34258270263672 48....</div><input id='attrs-bc02eab6-7637-48f0-912e-cd563f0c0df4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc02eab6-7637-48f0-912e-cd563f0c0df4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a32f3c2c-530e-4e6e-89c9-4aee9436edbc' class='xr-var-data-in' type='checkbox'><label for='data-a32f3c2c-530e-4e6e-89c9-4aee9436edbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:4326</dd></dl></div><div class='xr-var-data'><pre>array([&lt;POLYGON ((-95.343 48.547, -95.341 48.715, -95.094 48.717, -95.095 48.912, -...&gt;,\n",
-       "       &lt;POLYGON ((-118.851 47.95, -118.847 48.478, -118.869 48.479, -118.87 48.647,...&gt;,\n",
-       "       &lt;POLYGON ((-117.438 48.044, -117.541 48.043, -117.536 47.79, -117.607 47.798...&gt;,\n",
-       "       ...,\n",
-       "       &lt;POLYGON ((-76.396 37.108, -76.403 37.091, -76.434 37.089, -76.464 37.103, -...&gt;,\n",
-       "       &lt;POLYGON ((-77.532 38.565, -77.721 38.84, -77.707 38.877, -77.678 38.885, -7...&gt;,\n",
-       "       &lt;POLYGON ((-111.372 44.745, -111.368 45.35, -111.349 45.349, -111.349 45.635...&gt;],\n",
-       "      shape=(3085,), dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-60a3fc97-974e-4cde-93ac-a550ec4b2688' class='xr-section-summary-in' type='checkbox'  checked><label for='section-60a3fc97-974e-4cde-93ac-a550ec4b2688' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.119e+05 5.237e+04 ... 1.477e+04</div><input id='attrs-f3a962a9-7499-4886-a26b-e749ab5bcf0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3a962a9-7499-4886-a26b-e749ab5bcf0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cb07458-93c3-4657-ab61-813270c14511' class='xr-var-data-in' type='checkbox'><label for='data-9cb07458-93c3-4657-ab61-813270c14511' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>5</dd><dt><span>units :</span></dt><dd>m**2 s**-2</dd><dt><span>long_name :</span></dt><dd>Geopotential</dd><dt><span>standard_name :</span></dt><dd>geopotential</dd></dl></div><div class='xr-var-data'><pre>array([[[111869.99224043,  52373.79488647,  13605.52758194],\n",
-       "        [119183.82119804,  56513.86080846,  14691.14486816]],\n",
-       "\n",
-       "       [[114061.92714246,  54062.02176799,  14308.76377953],\n",
-       "        [118939.15480223,  56539.16121132,  14753.24585699]],\n",
-       "\n",
-       "       [[114083.92124268,  54078.8407858 ,  14317.38891687],\n",
-       "        [118977.3929111 ,  56559.86154093,  14758.99594854]],\n",
+       "    Info:         Monthly ERA-Interim data. Downloaded and edited by fabien.m...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-47e75a5e-15b4-4569-903d-dc217e95eb89' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-47e75a5e-15b4-4569-903d-dc217e95eb89' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>level</span>: 3</li><li><span class='xr-has-index'>month</span>: 2</li><li><span class='xr-has-index'>geometry</span>: 3085</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7131be73-5425-4d50-820a-90405b3a7947' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7131be73-5425-4d50-820a-90405b3a7947' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>200 500 850</div><input id='attrs-510eef9d-c976-4e5b-b5aa-8ba93ceccc2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-510eef9d-c976-4e5b-b5aa-8ba93ceccc2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53e72db7-1708-4a7b-a4f9-06c53a9a3e18' class='xr-var-data-in' type='checkbox'><label for='data-53e72db7-1708-4a7b-a4f9-06c53a9a3e18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([200, 500, 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 7</div><input id='attrs-a0822e96-576b-4df9-ab2e-e9bf57482324' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0822e96-576b-4df9-ab2e-e9bf57482324' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a00d0189-ed3f-496a-9538-333ce513981e' class='xr-var-data-in' type='checkbox'><label for='data-a00d0189-ed3f-496a-9538-333ce513981e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 7], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>geometry</span></div><div class='xr-var-dims'>(geometry)</div><div class='xr-var-dtype'>geometry</div><div class='xr-var-preview xr-preview'>POLYGON ((-95.34258270263672 48....</div><input id='attrs-4116ec85-ebab-48fd-98e3-0fa8207b3567' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4116ec85-ebab-48fd-98e3-0fa8207b3567' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06941e2c-497d-44df-a46c-8cfc2d4e7472' class='xr-var-data-in' type='checkbox'><label for='data-06941e2c-497d-44df-a46c-8cfc2d4e7472' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:4326</dd></dl></div><div class='xr-var-data'><pre>&lt;GeometryArray&gt;\n",
+       "[&lt;POLYGON ((-95.343 48.547, -95.341 48.715, -95.094 48.717, -95.095 48.912, -...&gt;,\n",
+       " &lt;POLYGON ((-118.851 47.95, -118.847 48.478, -118.869 48.479, -118.87 48.647,...&gt;,\n",
+       " &lt;POLYGON ((-117.438 48.044, -117.541 48.043, -117.536 47.79, -117.607 47.798...&gt;,\n",
+       " &lt;POLYGON ((-118.971 47.939, -118.973 47.96, -118.953 47.989, -118.953 48.02,...&gt;,\n",
+       " &lt;POLYGON ((-117.438 49, -117.031 49, -117.028 48.838, -117.038 48.046, -117....&gt;,\n",
+       " &lt;POLYGON ((-117.028 48.838, -117.031 49, -116.062 49, -116.056 48.499, -116....&gt;,\n",
+       " &lt;POLYGON ((-116.054 48.209, -116.056 48.499, -116.062 49, -114.728 49, -114....&gt;,\n",
+       " &lt;POLYGON ((-113.473 47.598, -113.636 47.6, -113.628 47.652, -113.602 47.669,...&gt;,\n",
+       " &lt;POLYGON ((-112.182 48.471, -112.228 48.479, -112.583 48.475, -112.587 48.3,...&gt;,\n",
+       " &lt;POLYGON ((-111.421 48.218, -111.673 48.213, -111.673 48.337, -111.799 48.33...&gt;,\n",
+       " ...\n",
+       " &lt;POLYGON ((-76.922 36.554, -76.924 36.554, -77.177 36.556, -77.32 36.554, -7...&gt;,\n",
+       " &lt;POLYGON ((-79.144 36.546, -79.217 36.55, -79.1 37.056, -79.037 37.03, -79.0...&gt;,\n",
+       " &lt;POLYGON ((-79.438 37.616, -79.458 37.603, -79.444 37.57, -79.467 37.552, -7...&gt;,\n",
+       " &lt;POLYGON ((-80.125 37.125, -80.14 37.128, -80.154 37.114, -80.168 37.112, -8...&gt;,\n",
+       " &lt;POLYGON ((-87.748 44.962, -87.84 44.927, -87.831 44.873, -87.986 44.72, -87...&gt;,\n",
+       " &lt;POLYGON ((-114.52 33.028, -114.558 33.037, -114.609 33.027, -114.633 33.034...&gt;,\n",
+       " &lt;POLYGON ((-107.195 34.584, -107.718 34.584, -108.227 34.583, -109.048 34.59...&gt;,\n",
+       " &lt;POLYGON ((-76.396 37.108, -76.403 37.091, -76.434 37.089, -76.464 37.103, -...&gt;,\n",
+       " &lt;POLYGON ((-77.532 38.565, -77.721 38.84, -77.707 38.877, -77.678 38.885, -7...&gt;,\n",
+       " &lt;POLYGON ((-111.372 44.745, -111.368 45.35, -111.349 45.349, -111.349 45.635...&gt;]\n",
+       "Length: 3085, dtype: geometry</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>STATE_NAME</span></div><div class='xr-var-dims'>(geometry)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Minnesota&#x27; ... &#x27;Montana&#x27;</div><input id='attrs-fd36832b-1786-49fe-88ac-e994dc713d7e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd36832b-1786-49fe-88ac-e994dc713d7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf533fe9-1e47-43bf-976c-92bec11e1275' class='xr-var-data-in' type='checkbox'><label for='data-cf533fe9-1e47-43bf-976c-92bec11e1275' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Minnesota&#x27;, &#x27;Washington&#x27;, &#x27;Washington&#x27;, ..., &#x27;Virginia&#x27;, &#x27;Virginia&#x27;,\n",
+       "       &#x27;Montana&#x27;], shape=(3085,), dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-26bbd7c5-a8ff-4901-96f4-9833072eeab2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26bbd7c5-a8ff-4901-96f4-9833072eeab2' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.116e+05 5.222e+04 ... 1.477e+04</div><input id='attrs-7589555f-9df1-44f8-802f-c3df2bba6ad3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7589555f-9df1-44f8-802f-c3df2bba6ad3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5edd1ae8-08bb-40d3-a347-13e91dc27bf4' class='xr-var-data-in' type='checkbox'><label for='data-5edd1ae8-08bb-40d3-a347-13e91dc27bf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>5</dd><dt><span>units :</span></dt><dd>m**2 s**-2</dd><dt><span>long_name :</span></dt><dd>Geopotential</dd><dt><span>standard_name :</span></dt><dd>geopotential</dd></dl></div><div class='xr-var-data'><pre>array([[[111648.61371544,  52224.86751511,  13554.92677623],\n",
+       "        [118961.86766389,  56394.25890405,  14650.31921809]],\n",
+       "\n",
+       "       [[            nan,             nan,             nan],\n",
+       "        [            nan,             nan,             nan]],\n",
+       "\n",
+       "       [[            nan,             nan,             nan],\n",
+       "        [            nan,             nan,             nan]],\n",
        "\n",
        "       ...,\n",
        "\n",
@@ -462,14 +478,14 @@
        "\n",
        "       [[114253.21352164,  54233.56616615,  14463.24957273],\n",
        "        [120142.07395624,  57200.99674968,  14769.53778307]]],\n",
-       "      shape=(3085, 2, 3))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.81 15.31 5.544 ... 12.0 0.9052</div><input id='attrs-6be68e5a-e001-4a02-b1fa-3e8d63d51fd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6be68e5a-e001-4a02-b1fa-3e8d63d51fd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc1bac6d-9029-4f06-acc9-18cdad0bfe3a' class='xr-var-data-in' type='checkbox'><label for='data-dc1bac6d-9029-4f06-acc9-18cdad0bfe3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>2</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[22.81261508, 15.31264735,  5.54431486],\n",
-       "        [25.63535833, 13.04690377,  4.17973121]],\n",
+       "      shape=(3085, 2, 3))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.19 14.94 5.344 ... 12.0 0.9052</div><input id='attrs-b31fea64-ed26-4040-a7e6-d4e68367e69f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b31fea64-ed26-4040-a7e6-d4e68367e69f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cb2f6c5-e8b2-49ec-8ecb-0a082e34c4a9' class='xr-var-data-in' type='checkbox'><label for='data-0cb2f6c5-e8b2-49ec-8ecb-0a082e34c4a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>2</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[22.18772699, 14.93755722,  5.3440571 ],\n",
+       "        [25.34335945, 12.9064088 ,  4.10948373]],\n",
        "\n",
-       "       [[22.79216992, 14.45840645,  2.20284111],\n",
-       "        [20.62550675, 10.59322195,  2.13521479]],\n",
+       "       [[        nan,         nan,         nan],\n",
+       "        [        nan,         nan,         nan]],\n",
        "\n",
-       "       [[22.8128772 , 14.49208855,  2.52891526],\n",
-       "        [20.78172877, 10.74944397,  2.29104364]],\n",
+       "       [[        nan,         nan,         nan],\n",
+       "        [        nan,         nan,         nan]],\n",
        "\n",
        "       ...,\n",
        "\n",
@@ -480,26 +496,25 @@
        "        [17.14615919,  9.79166667,  3.90870173]],\n",
        "\n",
        "       [[21.94448196, 14.4236322 ,  1.63876427],\n",
-       "        [24.29847176, 11.9962495 ,  0.90518479]]], shape=(3085, 2, 3))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.04 -8.724 ... 3.168 0.4852</div><input id='attrs-c817428f-cbab-494d-b2e0-4a64d900f479' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c817428f-cbab-494d-b2e0-4a64d900f479' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdc5a0ad-4248-4d06-ad6d-75a7d8218b79' class='xr-var-data-in' type='checkbox'><label for='data-bdc5a0ad-4248-4d06-ad6d-75a7d8218b79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>2</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.00364607e+01, -8.72388919e+00, -2.81253910e+00],\n",
-       "        [-5.01568747e+00, -3.74476592e+00, -9.08954785e-03]],\n",
+       "        [24.29847176, 11.9962495 ,  0.90518479]]], shape=(3085, 2, 3))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(geometry, month, level)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.41 -8.828 ... 3.168 0.4852</div><input id='attrs-45fe7475-ba40-4bff-955c-38a58de2eb50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45fe7475-ba40-4bff-955c-38a58de2eb50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32198535-0d5e-4a96-95fd-f6a19fe9c8d4' class='xr-var-data-in' type='checkbox'><label for='data-32198535-0d5e-4a96-95fd-f6a19fe9c8d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>number_of_significant_digits :</span></dt><dd>2</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[-10.40613412,  -8.82813358,  -2.78920556],\n",
+       "        [ -4.9766655 ,  -3.65620994,  -0.06252575]],\n",
        "\n",
-       "       [[-7.66129715e+00, -3.20052894e+00,  1.80463552e+00],\n",
-       "        [ 7.56252575e+00,  4.19023149e+00,  7.57731910e-01]],\n",
+       "       [[         nan,          nan,          nan],\n",
+       "        [         nan,          nan,          nan]],\n",
        "\n",
-       "       [[-7.77716850e+00, -3.22461903e+00,  2.08001911e+00],\n",
-       "        [ 7.67194653e+00,  4.28718913e+00,  8.63250492e-01]],\n",
+       "       [[         nan,          nan,          nan],\n",
+       "        [         nan,          nan,          nan]],\n",
        "\n",
        "       ...,\n",
        "\n",
-       "       [[ 3.71081876e+00,  2.75398422e+00, -3.91125710e-02],\n",
-       "        [-2.32046414e+00, -3.24132199e-01, -8.18774606e-02]],\n",
+       "       [[  3.71081876,   2.75398422,  -0.03911257],\n",
+       "        [ -2.32046414,  -0.3241322 ,  -0.08187746]],\n",
        "\n",
-       "       [[ 3.55473089e+00,  1.96613868e+00, -1.03632290e+00],\n",
-       "        [-2.41148885e+00, -9.63694264e-01, -6.22371513e-01]],\n",
+       "       [[  3.55473089,   1.96613868,  -1.0363229 ],\n",
+       "        [ -2.41148885,  -0.96369426,  -0.62237151]],\n",
        "\n",
-       "       [[-1.10625261e+01, -7.32639843e+00,  1.08859571e+00],\n",
-       "        [ 6.77598095e+00,  3.16833379e+00,  4.85215238e-01]]],\n",
-       "      shape=(3085, 2, 3))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c7fbced-f99a-4ac5-8740-ed01cf121482' class='xr-section-summary-in' type='checkbox'  ><label for='section-7c7fbced-f99a-4ac5-8740-ed01cf121482' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>level</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-09612940-ce47-4479-8d81-ad8fe27b0ac6' class='xr-index-data-in' type='checkbox'/><label for='index-09612940-ce47-4479-8d81-ad8fe27b0ac6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([200, 500, 850], dtype=&#x27;int32&#x27;, name=&#x27;level&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6c08222e-7024-455c-82f5-baf62d68ea2b' class='xr-index-data-in' type='checkbox'/><label for='index-6c08222e-7024-455c-82f5-baf62d68ea2b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 7], dtype=&#x27;int32&#x27;, name=&#x27;month&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>geometry</div></div><div class='xr-index-preview'>GeometryIndex (crs=EPSG:4326)</div><input type='checkbox' disabled/><label></label><input id='index-29a84bbc-66fe-42cd-9687-dc1acf1a802c' class='xr-index-data-in' type='checkbox'/><label for='index-29a84bbc-66fe-42cd-9687-dc1acf1a802c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>GeometryIndex(\n",
+       "       [[-11.06252607,  -7.32639843,   1.08859571],\n",
+       "        [  6.77598095,   3.16833379,   0.48521524]]], shape=(3085, 2, 3))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3bc54fbb-ddee-498d-9c9b-0c37509bc99c' class='xr-section-summary-in' type='checkbox'  ><label for='section-3bc54fbb-ddee-498d-9c9b-0c37509bc99c' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>level</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f890ef5b-73f4-4766-a3b1-463f21f99036' class='xr-index-data-in' type='checkbox'/><label for='index-f890ef5b-73f4-4766-a3b1-463f21f99036' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([200, 500, 850], dtype=&#x27;int32&#x27;, name=&#x27;level&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-86e46146-ccfc-4a78-a623-49a3f73e657f' class='xr-index-data-in' type='checkbox'/><label for='index-86e46146-ccfc-4a78-a623-49a3f73e657f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 7], dtype=&#x27;int32&#x27;, name=&#x27;month&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>geometry</div></div><div class='xr-index-preview'>GeometryIndex (crs=EPSG:4326)</div><input type='checkbox' disabled/><label></label><input id='index-c13fec18-c3c5-4ad2-b6ac-c8dc1c230038' class='xr-index-data-in' type='checkbox'/><label for='index-c13fec18-c3c5-4ad2-b6ac-c8dc1c230038' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>GeometryIndex(\n",
        "    [&lt;POLYGON ((-95.343 48.547, -95.341 48.715, -95.094 48.717, -95.095 48.912, -...&gt;\n",
        "     &lt;POLYGON ((-118.851 47.95, -118.847 48.478, -118.869 48.479, -118.87 48.647,...&gt;\n",
        "     &lt;POLYGON ((-117.438 48.044, -117.541 48.043, -117.536 47.79, -117.607 47.798...&gt;\n",
@@ -509,19 +524,20 @@
        "     &lt;POLYGON ((-76.396 37.108, -76.403 37.091, -76.434 37.089, -76.464 37.103, -...&gt;\n",
        "     &lt;POLYGON ((-77.532 38.565, -77.721 38.84, -77.707 38.877, -77.678 38.885, -7...&gt;\n",
        "     &lt;POLYGON ((-111.372 44.745, -111.368 45.35, -111.349 45.349, -111.349 45.635...&gt;],\n",
-       "    crs=EPSG:4326)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-458c2a32-d3eb-43af-834a-0fa01ef93c78' class='xr-section-summary-in' type='checkbox'  checked><label for='section-458c2a32-d3eb-43af-834a-0fa01ef93c78' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.0</dd><dt><span>Info :</span></dt><dd>Monthly ERA-Interim data. Downloaded and edited by fabien.maussion@uibk.ac.at</dd></dl></div></li></ul></div></div>"
+       "    crs=EPSG:4326)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80cfd022-0d7b-47c4-a0dc-12e385eba590' class='xr-section-summary-in' type='checkbox'  checked><label for='section-80cfd022-0d7b-47c4-a0dc-12e385eba590' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.0</dd><dt><span>Info :</span></dt><dd>Monthly ERA-Interim data. Downloaded and edited by fabien.maussion@uibk.ac.at</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset> Size: 469kB\n",
-       "Dimensions:   (geometry: 3085, month: 2, level: 3)\n",
+       "<xarray.Dataset> Size: 494kB\n",
+       "Dimensions:     (level: 3, month: 2, geometry: 3085)\n",
        "Coordinates:\n",
-       "  * level     (level) int32 12B 200 500 850\n",
-       "  * month     (month) int32 8B 1 7\n",
-       "  * geometry  (geometry) object 25kB POLYGON ((-95.34258270263672 48.54670333...\n",
+       "  * level       (level) int32 12B 200 500 850\n",
+       "  * month       (month) int32 8B 1 7\n",
+       "  * geometry    (geometry) geometry 25kB POLYGON ((-95.34258270263672 48.5467...\n",
+       "    STATE_NAME  (geometry) object 25kB 'Minnesota' 'Washington' ... 'Montana'\n",
        "Data variables:\n",
-       "    z         (geometry, month, level) float64 148kB 1.119e+05 ... 1.477e+04\n",
-       "    u         (geometry, month, level) float64 148kB 22.81 15.31 ... 12.0 0.9052\n",
-       "    v         (geometry, month, level) float64 148kB -10.04 -8.724 ... 0.4852\n",
+       "    z           (geometry, month, level) float64 148kB 1.116e+05 ... 1.477e+04\n",
+       "    u           (geometry, month, level) float64 148kB 22.19 14.94 ... 0.9052\n",
+       "    v           (geometry, month, level) float64 148kB -10.41 -8.828 ... 0.4852\n",
        "Indexes:\n",
        "    geometry  GeometryIndex (crs=EPSG:4326)\n",
        "Attributes:\n",
@@ -539,10 +555,10 @@
     "counties = gpd.read_file(geodatasets.get_path(\"geoda natregimes\")).to_crs(4326)\n",
     "\n",
     "aggregated = ds.xvec.zonal_stats(\n",
-    "    counties.geometry,\n",
+    "    counties.set_index(\"STATE_NAME\").geometry,\n",
     "    x_coords=\"longitude\",\n",
     "    y_coords=\"latitude\",\n",
-    "    method=\"iterate\",  # polygons are small compared to pixels\n",
+    "    # method=\"iterate\",  # polygons are small compared to pixels\n",
     "    all_touched=True,\n",
     ")\n",
     "aggregated"
@@ -631,6 +647,33 @@
     "f, ax = aggregated.v.xvec.plot(col=\"month\", row=\"level\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When slicing down to a 1-D array, no arguments are needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 300x159.127 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "f, ax = aggregated.z.sel(level=200, month=1).xvec.plot()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -642,7 +685,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -1029,16 +1072,16 @@
        "    fwidth       (name, year) float64 120B 1.254e+03 470.1 888.4 ... 279.4 202.6\n",
        "    geometry     (name, year) object 120B POLYGON ((432375.11039999966 876165...\n",
        "Indexes:\n",
-       "    spatial_ref  CRSIndex (crs=EPSG:32633)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ddb58843-4c83-4fc9-abcf-d1d604ab4861' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ddb58843-4c83-4fc9-abcf-d1d604ab4861' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>name</span>: 5</li><li><span class='xr-has-index'>year</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d7adb67c-046f-43d6-9aa3-22edb8f67484' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7adb67c-046f-43d6-9aa3-22edb8f67484' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>name</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Austre Brøggerbreen&#x27; ... &#x27;Steen...</div><input id='attrs-e97ebb4e-b458-4b90-b237-34da859c2dca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e97ebb4e-b458-4b90-b237-34da859c2dca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac181a9-3e34-4e7d-bb67-fe379f1ccfac' class='xr-var-data-in' type='checkbox'><label for='data-5ac181a9-3e34-4e7d-bb67-fe379f1ccfac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
-       "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.936e+03 1.99e+03 2.007e+03</div><input id='attrs-11f33183-c006-4bee-812e-b75d590e68e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11f33183-c006-4bee-812e-b75d590e68e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6fdd27-6ea8-449f-9da2-7295d5ce6c3e' class='xr-var-data-in' type='checkbox'><label for='data-4c6fdd27-6ea8-449f-9da2-7295d5ce6c3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1936., 1990., 2007.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-2e44e244-4ff8-41cd-aa48-45e6e06ed122' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e44e244-4ff8-41cd-aa48-45e6e06ed122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a32d3ed-baf1-415e-b5b4-2f8f11e76a6f' class='xr-var-data-in' type='checkbox'><label for='data-9a32d3ed-baf1-415e-b5b4-2f8f11e76a6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9b56fd98-386c-472d-ba65-2432b5f4fbeb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b56fd98-386c-472d-ba65-2432b5f4fbeb' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>length</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.808e+03 5.265e+03 ... 1.819e+03</div><input id='attrs-ea200830-687b-4b08-80d1-a72c0b63e856' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea200830-687b-4b08-80d1-a72c0b63e856' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5fabbf3-1329-41aa-9d94-f73920cc5636' class='xr-var-data-in' type='checkbox'><label for='data-d5fabbf3-1329-41aa-9d94-f73920cc5636' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5808.299579, 5265.479773, 4886.823854],\n",
+       "    spatial_ref  CRSIndex (crs=EPSG:32633)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1c401521-8619-4342-a510-36739631eca8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1c401521-8619-4342-a510-36739631eca8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>name</span>: 5</li><li><span class='xr-has-index'>year</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4a6f7090-d597-4cc5-9bd2-e6f46f6a87a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4a6f7090-d597-4cc5-9bd2-e6f46f6a87a3' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>name</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Austre Brøggerbreen&#x27; ... &#x27;Steen...</div><input id='attrs-a232ed5f-1610-4708-a30c-8ea091718b40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a232ed5f-1610-4708-a30c-8ea091718b40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd121bb2-2b39-4219-9893-a82eeccdf49d' class='xr-var-data-in' type='checkbox'><label for='data-dd121bb2-2b39-4219-9893-a82eeccdf49d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
+       "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.936e+03 1.99e+03 2.007e+03</div><input id='attrs-cf56956f-c823-420e-b8a0-1dd4821d04b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf56956f-c823-420e-b8a0-1dd4821d04b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-452861de-f40f-48db-820a-390ad7a83273' class='xr-var-data-in' type='checkbox'><label for='data-452861de-f40f-48db-820a-390ad7a83273' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1936., 1990., 2007.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-7a4fea84-a6be-4753-a70d-b40fb816baef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7a4fea84-a6be-4753-a70d-b40fb816baef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb516eb-b897-4428-bf89-c30bedff989c' class='xr-var-data-in' type='checkbox'><label for='data-ecb516eb-b897-4428-bf89-c30bedff989c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b4c2e8a-2768-463e-bb04-720c7591bf0f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b4c2e8a-2768-463e-bb04-720c7591bf0f' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>length</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.808e+03 5.265e+03 ... 1.819e+03</div><input id='attrs-94378c63-0879-41d6-8a3a-8cadeedca6a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94378c63-0879-41d6-8a3a-8cadeedca6a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ab82aa9-2c26-4cff-9453-80299a2142bc' class='xr-var-data-in' type='checkbox'><label for='data-8ab82aa9-2c26-4cff-9453-80299a2142bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5808.299579, 5265.479773, 4886.823854],\n",
        "       [4655.052772, 3751.333493, 3441.045428],\n",
        "       [5029.248703, 4335.833494, 4099.017543],\n",
        "       [4381.553508, 3772.578735, 3566.190758],\n",
-       "       [2279.163326, 1928.610561, 1818.691555]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwidth</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.254e+03 470.1 ... 279.4 202.6</div><input id='attrs-8b5aad1d-4605-4302-be36-d39c56afc17d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8b5aad1d-4605-4302-be36-d39c56afc17d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2fa9332-d1be-4359-9d5e-93a818bbc415' class='xr-var-data-in' type='checkbox'><label for='data-d2fa9332-d1be-4359-9d5e-93a818bbc415' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1254.324348,  470.127452,  888.406938],\n",
+       "       [2279.163326, 1928.610561, 1818.691555]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwidth</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.254e+03 470.1 ... 279.4 202.6</div><input id='attrs-391fe7bb-25ab-4275-9c93-6e42a55fb7b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-391fe7bb-25ab-4275-9c93-6e42a55fb7b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3506eaa9-ca1e-4382-94a0-680716a88c28' class='xr-var-data-in' type='checkbox'><label for='data-3506eaa9-ca1e-4382-94a0-680716a88c28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1254.324348,  470.127452,  888.406938],\n",
        "       [1215.71829 ,  415.68072 ,  552.597872],\n",
        "       [ 465.073176,  428.611163,  414.354343],\n",
        "       [1448.993086,  778.749748,  698.536216],\n",
-       "       [ 208.142946,  279.3527  ,  202.641662]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((432375.11039999966 876...</div><input id='attrs-e6ae2ad7-391e-4bbe-91cb-533982bf12f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6ae2ad7-391e-4bbe-91cb-533982bf12f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87a5adea-5fea-4828-9629-d9e80edc2eb3' class='xr-var-data-in' type='checkbox'><label for='data-87a5adea-5fea-4828-9629-d9e80edc2eb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&lt;POLYGON ((432375.11 8761657.493, 432374.075 8761556.916, 432359.094 8761317...&gt;,\n",
+       "       [ 208.142946,  279.3527  ,  202.641662]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((432375.11039999966 876...</div><input id='attrs-707a9294-70f8-433e-ad4d-ed73852dc749' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-707a9294-70f8-433e-ad4d-ed73852dc749' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca47b7d6-4b8c-43d1-9c7b-80d77e12c8e1' class='xr-var-data-in' type='checkbox'><label for='data-ca47b7d6-4b8c-43d1-9c7b-80d77e12c8e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&lt;POLYGON ((432375.11 8761657.493, 432374.075 8761556.916, 432359.094 8761317...&gt;,\n",
        "        &lt;POLYGON ((432827.911 8760071.745, 432927.89 8760033.48, 432969.69 8760016.4...&gt;,\n",
        "        &lt;POLYGON ((430859.331 8760810.068, 430859.331 8760955.06, 430896.373 8761011...&gt;],\n",
        "       [&lt;POLYGON ((439050.076 8760008.254, 439165.072 8760005.234, 439280.066 875999...&gt;,\n",
@@ -1053,9 +1096,9 @@
        "       [&lt;POLYGON ((433846.077 8756899.896, 434061.106 8756825.509, 434270.08 8756730...&gt;,\n",
        "        &lt;POLYGON ((433722.085 8756919.211, 433772.071 8756919.991, 433782.204 875692...&gt;,\n",
        "        &lt;POLYGON ((433151.47 8756599.749, 433235.124 8756697.643, 433284.108 8756749...&gt;]],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0154b42-0279-4cdf-b685-dbf8fd1488a3' class='xr-section-summary-in' type='checkbox'  ><label for='section-d0154b42-0279-4cdf-b685-dbf8fd1488a3' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>name</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c465b47a-8735-457a-830f-344c094eb810' class='xr-index-data-in' type='checkbox'/><label for='index-c465b47a-8735-457a-830f-344c094eb810' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-00eb4d27-0604-471c-a434-73815e145b83' class='xr-section-summary-in' type='checkbox'  ><label for='section-00eb4d27-0604-471c-a434-73815e145b83' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>name</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e8463c90-7cd2-4e8f-bd21-26a96cf15914' class='xr-index-data-in' type='checkbox'/><label for='index-e8463c90-7cd2-4e8f-bd21-26a96cf15914' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
        "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;name&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6bf6c73e-cf64-486d-bfd8-154e11cb9cd0' class='xr-index-data-in' type='checkbox'/><label for='index-6bf6c73e-cf64-486d-bfd8-154e11cb9cd0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1936.0, 1990.0, 2007.0], dtype=&#x27;float64&#x27;, name=&#x27;year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spatial_ref</div></div><div class='xr-index-preview'>CRSIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-9ef88a66-f19f-42c5-8adb-8c3e0584b25e' class='xr-index-data-in' type='checkbox'/><label for='index-9ef88a66-f19f-42c5-8adb-8c3e0584b25e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>CRSIndex\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;name&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-261cf75f-c222-4d30-a431-40970b4ad5cb' class='xr-index-data-in' type='checkbox'/><label for='index-261cf75f-c222-4d30-a431-40970b4ad5cb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1936.0, 1990.0, 2007.0], dtype=&#x27;float64&#x27;, name=&#x27;year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spatial_ref</div></div><div class='xr-index-preview'>CRSIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-54d110e3-d81c-4c9f-a8d1-502d6d860b2d' class='xr-index-data-in' type='checkbox'/><label for='index-54d110e3-d81c-4c9f-a8d1-502d6d860b2d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>CRSIndex\n",
        "&lt;Projected CRS: EPSG:32633&gt;\n",
        "Name: WGS 84 / UTM zone 33N\n",
        "Axis Info [cartesian]:\n",
@@ -1070,7 +1113,7 @@
        "Datum: World Geodetic System 1984 ensemble\n",
        "- Ellipsoid: WGS 84\n",
        "- Prime Meridian: Greenwich\n",
-       "</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e23c4ed5-691b-4bbc-af05-4f4bcb12ab23' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e23c4ed5-691b-4bbc-af05-4f4bcb12ab23' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5a0d2b07-4d25-438a-9e75-e91475aa3780' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5a0d2b07-4d25-438a-9e75-e91475aa3780' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 432B\n",
@@ -1087,7 +1130,7 @@
        "    spatial_ref  CRSIndex (crs=EPSG:32633)"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1111,7 +1154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -1138,7 +1181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -1165,7 +1208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -1192,7 +1235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -1210,6 +1253,33 @@
     "f, ax = glaciers.xvec.plot(col=\"year\", geometry=\"geometry\", hue=\"fwidth\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Or with categorical data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x211.901 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "f, ax = glaciers.xvec.plot(col=\"year\", geometry=\"geometry\", hue=\"name\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1221,7 +1291,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -1610,21 +1680,21 @@
        "    geometry          (name, year) object 120B POLYGON ((432375.11039999966 8...\n",
        "Indexes:\n",
        "    spatial_ref       CRSIndex (crs=EPSG:32633)\n",
-       "    summary_geometry  GeometryIndex (crs=EPSG:32633)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1f2f69c1-d1a5-45f6-a278-fd37315b0b42' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1f2f69c1-d1a5-45f6-a278-fd37315b0b42' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>name</span>: 5</li><li><span class='xr-has-index'>year</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-88feb24c-1e54-41a8-9e99-1e917779e1c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-88feb24c-1e54-41a8-9e99-1e917779e1c1' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>name</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Austre Brøggerbreen&#x27; ... &#x27;Steen...</div><input id='attrs-545f0580-909c-44b7-a458-3265fe4df7cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-545f0580-909c-44b7-a458-3265fe4df7cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecda5802-668b-4ed9-b18c-5019d239f313' class='xr-var-data-in' type='checkbox'><label for='data-ecda5802-668b-4ed9-b18c-5019d239f313' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
-       "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.936e+03 1.99e+03 2.007e+03</div><input id='attrs-18587c98-a75f-457c-af72-9b212a2d3559' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-18587c98-a75f-457c-af72-9b212a2d3559' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d89544f4-e4bb-4726-a108-21274cca8ee3' class='xr-var-data-in' type='checkbox'><label for='data-d89544f4-e4bb-4726-a108-21274cca8ee3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1936., 1990., 2007.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a9a7d004-09c0-4c6f-89b2-f78e32a8d008' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9a7d004-09c0-4c6f-89b2-f78e32a8d008' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-120be617-1834-4084-a0ec-f5f6e80c2493' class='xr-var-data-in' type='checkbox'><label for='data-120be617-1834-4084-a0ec-f5f6e80c2493' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>summary_geometry</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((431324.8682000004 8762...</div><input id='attrs-d77796ff-3382-4aa1-8435-865efbe904fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d77796ff-3382-4aa1-8435-865efbe904fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21c63596-6ed6-4b6a-b32e-3210cd060ccf' class='xr-var-data-in' type='checkbox'><label for='data-21c63596-6ed6-4b6a-b32e-3210cd060ccf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32633</dd></dl></div><div class='xr-var-data'><pre>array([&lt;POLYGON ((431324.868 8762430.398, 431365.555 8762561.178, 431505.103 876253...&gt;,\n",
+       "    summary_geometry  GeometryIndex (crs=EPSG:32633)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2f7307f4-5d9b-4a5c-a2ce-73bf86c9ac24' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2f7307f4-5d9b-4a5c-a2ce-73bf86c9ac24' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>name</span>: 5</li><li><span class='xr-has-index'>year</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a1be7dc3-b87f-474a-a7ed-4ef6467e3d4f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a1be7dc3-b87f-474a-a7ed-4ef6467e3d4f' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>name</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Austre Brøggerbreen&#x27; ... &#x27;Steen...</div><input id='attrs-c1a44bb2-4732-4655-bdc9-dbd7afd5feb2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c1a44bb2-4732-4655-bdc9-dbd7afd5feb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e016b48a-eb4a-4ed3-b294-de0fa809eca3' class='xr-var-data-in' type='checkbox'><label for='data-e016b48a-eb4a-4ed3-b294-de0fa809eca3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
+       "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.936e+03 1.99e+03 2.007e+03</div><input id='attrs-aed8e54a-9d01-46ce-bcab-550e345cf122' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aed8e54a-9d01-46ce-bcab-550e345cf122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02dbc670-4858-40a5-81e1-12ebb2fb88ba' class='xr-var-data-in' type='checkbox'><label for='data-02dbc670-4858-40a5-81e1-12ebb2fb88ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1936., 1990., 2007.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-20cfa29e-7018-43eb-9e34-67d172b452e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-20cfa29e-7018-43eb-9e34-67d172b452e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5540106b-26b1-4328-bf02-f1b1df61d57b' class='xr-var-data-in' type='checkbox'><label for='data-5540106b-26b1-4328-bf02-f1b1df61d57b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>summary_geometry</span></div><div class='xr-var-dims'>(name)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((431324.8682000004 8762...</div><input id='attrs-2f774553-98b2-4f46-b693-73d9b0fa64e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f774553-98b2-4f46-b693-73d9b0fa64e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c7724d9-eab8-4486-8122-5332b243ac40' class='xr-var-data-in' type='checkbox'><label for='data-8c7724d9-eab8-4486-8122-5332b243ac40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32633</dd></dl></div><div class='xr-var-data'><pre>array([&lt;POLYGON ((431324.868 8762430.398, 431365.555 8762561.178, 431505.103 876253...&gt;,\n",
        "       &lt;POLYGON ((437890.08 8759688.247, 437972.08 8759783.098, 438111.093 8759913....&gt;,\n",
        "       &lt;POLYGON ((435306.075 8755348.831, 435469.097 8755538.298, 435588.071 875565...&gt;,\n",
        "       &lt;POLYGON ((436099.83 8760609.829, 436157.072 8760718.862, 436363.409 8760819...&gt;,\n",
        "       &lt;POLYGON ((433235.124 8756697.643, 433284.108 8756749.624, 433305.082 875676...&gt;],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2868082-4054-4eb7-a4ec-589ff4c8db5b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2868082-4054-4eb7-a4ec-589ff4c8db5b' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>length</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.808e+03 5.265e+03 ... 1.819e+03</div><input id='attrs-bba0d8af-8f6d-4f05-9bef-9bdd806ab588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bba0d8af-8f6d-4f05-9bef-9bdd806ab588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-790febd0-6eb2-4681-8bd2-d4e544b1ba37' class='xr-var-data-in' type='checkbox'><label for='data-790febd0-6eb2-4681-8bd2-d4e544b1ba37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5808.299579, 5265.479773, 4886.823854],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4759913e-0980-4f55-be31-ececd75a9cb3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4759913e-0980-4f55-be31-ececd75a9cb3' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>length</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.808e+03 5.265e+03 ... 1.819e+03</div><input id='attrs-2c271bce-8a68-497d-9b18-b9c6f031307e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c271bce-8a68-497d-9b18-b9c6f031307e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cbacad2-e3ed-43a1-99cd-9549fa338a40' class='xr-var-data-in' type='checkbox'><label for='data-9cbacad2-e3ed-43a1-99cd-9549fa338a40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5808.299579, 5265.479773, 4886.823854],\n",
        "       [4655.052772, 3751.333493, 3441.045428],\n",
        "       [5029.248703, 4335.833494, 4099.017543],\n",
        "       [4381.553508, 3772.578735, 3566.190758],\n",
-       "       [2279.163326, 1928.610561, 1818.691555]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwidth</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.254e+03 470.1 ... 279.4 202.6</div><input id='attrs-4ea264f1-f7f8-42b7-a659-32d31f5eb4f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ea264f1-f7f8-42b7-a659-32d31f5eb4f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5ad0f5b-d02d-40a9-aa61-905486fab5eb' class='xr-var-data-in' type='checkbox'><label for='data-a5ad0f5b-d02d-40a9-aa61-905486fab5eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1254.324348,  470.127452,  888.406938],\n",
+       "       [2279.163326, 1928.610561, 1818.691555]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwidth</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.254e+03 470.1 ... 279.4 202.6</div><input id='attrs-28c71083-f995-433b-a818-dc8f1e5e4b98' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28c71083-f995-433b-a818-dc8f1e5e4b98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15eacfa1-7c6b-408d-b0d7-447d6d06d15b' class='xr-var-data-in' type='checkbox'><label for='data-15eacfa1-7c6b-408d-b0d7-447d6d06d15b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1254.324348,  470.127452,  888.406938],\n",
        "       [1215.71829 ,  415.68072 ,  552.597872],\n",
        "       [ 465.073176,  428.611163,  414.354343],\n",
        "       [1448.993086,  778.749748,  698.536216],\n",
-       "       [ 208.142946,  279.3527  ,  202.641662]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((432375.11039999966 876...</div><input id='attrs-10ad6774-a145-4dac-9d83-c6d7779fbc26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10ad6774-a145-4dac-9d83-c6d7779fbc26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb7ed9a1-05bc-459a-9af0-d65b7f497201' class='xr-var-data-in' type='checkbox'><label for='data-cb7ed9a1-05bc-459a-9af0-d65b7f497201' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&lt;POLYGON ((432375.11 8761657.493, 432374.075 8761556.916, 432359.094 8761317...&gt;,\n",
+       "       [ 208.142946,  279.3527  ,  202.641662]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>(name, year)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>POLYGON ((432375.11039999966 876...</div><input id='attrs-6591e5b3-b6ec-4786-b943-ea8d57d85e85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6591e5b3-b6ec-4786-b943-ea8d57d85e85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f817a2e-c403-4660-9dea-72fde0e14364' class='xr-var-data-in' type='checkbox'><label for='data-3f817a2e-c403-4660-9dea-72fde0e14364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&lt;POLYGON ((432375.11 8761657.493, 432374.075 8761556.916, 432359.094 8761317...&gt;,\n",
        "        &lt;POLYGON ((432827.911 8760071.745, 432927.89 8760033.48, 432969.69 8760016.4...&gt;,\n",
        "        &lt;POLYGON ((430859.331 8760810.068, 430859.331 8760955.06, 430896.373 8761011...&gt;],\n",
        "       [&lt;POLYGON ((439050.076 8760008.254, 439165.072 8760005.234, 439280.066 875999...&gt;,\n",
@@ -1639,9 +1709,9 @@
        "       [&lt;POLYGON ((433846.077 8756899.896, 434061.106 8756825.509, 434270.08 8756730...&gt;,\n",
        "        &lt;POLYGON ((433722.085 8756919.211, 433772.071 8756919.991, 433782.204 875692...&gt;,\n",
        "        &lt;POLYGON ((433151.47 8756599.749, 433235.124 8756697.643, 433284.108 8756749...&gt;]],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1e649f5a-bcfc-4235-8379-d6934e6b9d0c' class='xr-section-summary-in' type='checkbox'  ><label for='section-1e649f5a-bcfc-4235-8379-d6934e6b9d0c' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>name</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-cf0a05ab-bc39-4060-adee-c8fe64f927ab' class='xr-index-data-in' type='checkbox'/><label for='index-cf0a05ab-bc39-4060-adee-c8fe64f927ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed0c5419-c0f3-43cb-b772-8c713502e8bb' class='xr-section-summary-in' type='checkbox'  ><label for='section-ed0c5419-c0f3-43cb-b772-8c713502e8bb' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>name</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-450803f3-bcad-43cb-bd79-e39757a0cb5f' class='xr-index-data-in' type='checkbox'/><label for='index-450803f3-bcad-43cb-bd79-e39757a0cb5f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Austre Brøggerbreen&#x27;, &#x27;Austre Lovenbreen&#x27;, &#x27;Edithbreen&#x27;,\n",
        "       &#x27;Midtre Lovenbreen&#x27;, &#x27;Steenbreen&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;name&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-099ee2ff-2a23-4522-b751-ac0b2365ae83' class='xr-index-data-in' type='checkbox'/><label for='index-099ee2ff-2a23-4522-b751-ac0b2365ae83' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1936.0, 1990.0, 2007.0], dtype=&#x27;float64&#x27;, name=&#x27;year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spatial_ref</div></div><div class='xr-index-preview'>CRSIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-d387f880-5fa3-40fc-a095-6b0d7dfb2519' class='xr-index-data-in' type='checkbox'/><label for='index-d387f880-5fa3-40fc-a095-6b0d7dfb2519' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>CRSIndex\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;name&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3419ca6d-9781-4b38-b63b-32c4a53b3ad9' class='xr-index-data-in' type='checkbox'/><label for='index-3419ca6d-9781-4b38-b63b-32c4a53b3ad9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1936.0, 1990.0, 2007.0], dtype=&#x27;float64&#x27;, name=&#x27;year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spatial_ref</div></div><div class='xr-index-preview'>CRSIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-d4f42d8e-ac98-44d9-a02e-1ac631e562c4' class='xr-index-data-in' type='checkbox'/><label for='index-d4f42d8e-ac98-44d9-a02e-1ac631e562c4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>CRSIndex\n",
        "&lt;Projected CRS: EPSG:32633&gt;\n",
        "Name: WGS 84 / UTM zone 33N\n",
        "Axis Info [cartesian]:\n",
@@ -1656,13 +1726,13 @@
        "Datum: World Geodetic System 1984 ensemble\n",
        "- Ellipsoid: WGS 84\n",
        "- Prime Meridian: Greenwich\n",
-       "</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>summary_geometry</div></div><div class='xr-index-preview'>GeometryIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-9b8244a9-277b-44cf-8880-5c54cca8df4f' class='xr-index-data-in' type='checkbox'/><label for='index-9b8244a9-277b-44cf-8880-5c54cca8df4f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>GeometryIndex(\n",
+       "</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>summary_geometry</div></div><div class='xr-index-preview'>GeometryIndex (crs=EPSG:32633)</div><input type='checkbox' disabled/><label></label><input id='index-054a0123-e8ca-4c3e-87f1-7d561c7ef55a' class='xr-index-data-in' type='checkbox'/><label for='index-054a0123-e8ca-4c3e-87f1-7d561c7ef55a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>GeometryIndex(\n",
        "    [&lt;POLYGON ((431324.868 8762430.398, 431365.555 8762561.178, 431505.103 876253...&gt;\n",
        "     &lt;POLYGON ((437890.08 8759688.247, 437972.08 8759783.098, 438111.093 8759913....&gt;\n",
        "     &lt;POLYGON ((435306.075 8755348.831, 435469.097 8755538.298, 435588.071 875565...&gt;\n",
        "     &lt;POLYGON ((436099.83 8760609.829, 436157.072 8760718.862, 436363.409 8760819...&gt;\n",
        "     &lt;POLYGON ((433235.124 8756697.643, 433284.108 8756749.624, 433305.082 875676...&gt;],\n",
-       "    crs=EPSG:32633)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6be67d8a-921e-4254-a3b9-8a6d965e633f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6be67d8a-921e-4254-a3b9-8a6d965e633f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "    crs=EPSG:32633)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3f02941e-3374-4ac4-a947-e52e28535447' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3f02941e-3374-4ac4-a947-e52e28535447' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 472B\n",
@@ -1681,7 +1751,7 @@
        "    summary_geometry  GeometryIndex (crs=EPSG:32633)"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1702,7 +1772,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -1729,7 +1799,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -1748,13 +1818,6 @@
     "    col=\"year\", geometry=\"summary_geometry\", hue=\"fwidth\"\n",
     ")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -1773,7 +1836,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.1"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,
diff --git a/xvec/plotting.py b/xvec/plotting.py
index 5f885f5..523f496 100644
--- a/xvec/plotting.py
+++ b/xvec/plotting.py
@@ -78,23 +78,55 @@ def _get_crs(arr, geometry=None):
     )
 
 
-def _setup_colorbar(fig, cmap_params, label=None):
+def _setup_legend(fig, cmap_params, label=None):
     from matplotlib import cm
     from matplotlib.colors import Normalize
+    from matplotlib.lines import Line2D
 
-    if not cmap_params["norm"]:
-        cmap_params["norm"] = Normalize(
-            vmin=cmap_params["vmin"], vmax=cmap_params["vmax"]
+    if "norm" in cmap_params:
+        if not cmap_params["norm"]:
+            cmap_params["norm"] = Normalize(
+                vmin=cmap_params["vmin"], vmax=cmap_params["vmax"]
+            )
+        n_cmap = cm.ScalarMappable(norm=cmap_params["norm"], cmap=cmap_params["cmap"])
+        fig.subplots_adjust(right=0.85)
+        cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
+        fig.colorbar(
+            n_cmap,
+            cax=cbar_ax,
+            label=label,
+            extend=cmap_params["extend"],
+        )
+    else:
+        if "cmap" not in cmap_params:
+            cmap_params["cmap"] = "tab10"
+
+        mn = 0
+        mx = len(cmap_params["categories"]) - 1
+
+        norm = Normalize(vmin=mn, vmax=mx)
+
+        n_cmap = cm.ScalarMappable(cmap=cmap_params["cmap"], norm=norm)
+        patches = []
+        for i in range(len(cmap_params["categories"])):
+            patches.append(
+                Line2D(
+                    [0],
+                    [0],
+                    linestyle="none",
+                    marker="o",
+                    markersize=10,
+                    markerfacecolor=n_cmap.to_rgba(i),
+                    markeredgewidth=0,
+                )
+            )
+        fig.get_axes()[-1].legend(
+            numpoints=1,
+            loc="upper left",
+            handles=patches,
+            labels=list(cmap_params["categories"]),
+            bbox_to_anchor=(1.1, 1.05),
         )
-    n_cmap = cm.ScalarMappable(norm=cmap_params["norm"], cmap=cmap_params["cmap"])
-    fig.subplots_adjust(right=0.85)
-    cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
-    fig.colorbar(
-        n_cmap,
-        cax=cbar_ax,
-        label=label,
-        extend=cmap_params["extend"],
-    )
 
 
 def _plot_faceted(arr, axs, row, col, hue, geometry, cmap_params=None, **kwargs):
@@ -148,9 +180,10 @@ def _plot_single_panel(arr, ax, hue, geometry, cmap_params, **kwargs):
             sub.xvec.to_geodataframe(geometry=geometry).plot(
                 vals,
                 ax=ax,
-                vmin=cmap_params["vmin"],
-                vmax=cmap_params["vmax"],
-                cmap=cmap_params["cmap"],
+                vmin=cmap_params.get("vmin", None),
+                vmax=cmap_params.get("vmax", None),
+                cmap=cmap_params.get("cmap", None),
+                categories=cmap_params.get("categories", None),
                 **kwargs,
             )
         else:
@@ -160,9 +193,10 @@ def _plot_single_panel(arr, ax, hue, geometry, cmap_params, **kwargs):
             arr.xvec.to_geodataframe().reset_index().plot(
                 hue,
                 ax=ax,
-                vmin=cmap_params["vmin"],
-                vmax=cmap_params["vmax"],
-                cmap=cmap_params["cmap"],
+                vmin=cmap_params.get("vmin", None),
+                vmax=cmap_params.get("vmax", None),
+                cmap=cmap_params.get("cmap", None),
+                categories=cmap_params.get("categories", None),
                 **kwargs,
             )
         else:
@@ -173,9 +207,10 @@ def _plot_single_panel(arr, ax, hue, geometry, cmap_params, **kwargs):
         arr.xvec.to_geodataframe(name=name, geometry=geometry).plot(
             name,
             ax=ax,
-            vmin=cmap_params["vmin"],
-            vmax=cmap_params["vmax"],
-            cmap=cmap_params["cmap"],
+            vmin=cmap_params.get("vmin", None),
+            vmax=cmap_params.get("vmax", None),
+            cmap=cmap_params.get("cmap", None),
+            categories=cmap_params.get("categories", None),
             **kwargs,
         )
 
@@ -200,8 +235,6 @@ def _plot(
     norm=None,
     **kwargs,
 ):
-    # TODO: support plotting of categorical data
-
     # Calculate grid dimensions
     if row and col:
         n_rows, n_cols = arr[row].shape[0], arr[col].shape[0]
@@ -220,37 +253,32 @@ def _plot(
     fig, axs = _setup_axes(n_rows, n_cols, arr, geometry, crs, subplot_kws, figsize)
 
     # Setup color parameters if needed
-    cmap_params = (
-        _determine_cmap_params(
-            arr[hue].data,
-            vmin=vmin,
-            vmax=vmax,
-            cmap=cmap,
-            center=center,
-            robust=robust,
-            extend=extend,
-            levels=levels,
-            norm=norm,
-        )
-        if hue
-        else None
-    )
-    if (
+    if hue or (
         not hue
         and isinstance(arr, xr.DataArray)
         and not np.all(shapely.is_valid_input(arr.data))
     ):
-        cmap_params = _determine_cmap_params(
-            arr.data,
-            vmin=vmin,
-            vmax=vmax,
-            cmap=cmap,
-            center=center,
-            robust=robust,
-            extend=extend,
-            levels=levels,
-            norm=norm,
-        )
+        array = arr[hue].data if hue else arr.data
+
+        # object is categorical, not supported by _determine_cmap_params
+        if array.dtype != "object":
+            cmap_params = _determine_cmap_params(
+                array,
+                vmin=vmin,
+                vmax=vmax,
+                cmap=cmap,
+                center=center,
+                robust=robust,
+                extend=extend,
+                levels=levels,
+                norm=norm,
+            )
+        else:
+            cmap_params = {"categories": np.unique(array)}
+            if cmap:
+                cmap_params["cmap"] = cmap
+    else:
+        cmap_params = {}
 
     # Handle simple case - single geometry with no faceting
     if not col and geometry in arr.xvec._geom_coords_all:
@@ -261,6 +289,22 @@ def _plot(
         axs.set_ylabel(y_label, fontsize="small")
         return fig, axs
 
+    if not col and arr.ndim == 1:
+        arr.xvec.to_geodataframe().plot(arr.values, ax=axs, **kwargs)
+        axs.set_xlabel(x_label, fontsize="small")
+        axs.set_ylabel(y_label, fontsize="small")
+
+        # Add colorbar if needed
+        if hue:
+            _setup_legend(fig, cmap_params, label=hue)
+        elif (
+            isinstance(arr, xr.DataArray)
+            and not geometry
+            and not np.all(shapely.is_valid_input(arr))
+        ):
+            _setup_legend(fig, cmap_params, label=label_from_attrs(arr))
+        return fig, axs
+
     # Handle faceted plotting
     used_axes = _plot_faceted(arr, axs, row, col, hue, geometry, cmap_params, **kwargs)
 
@@ -278,12 +322,12 @@ def _plot(
 
     # Add colorbar if needed
     if hue:
-        _setup_colorbar(fig, cmap_params, label=hue)
+        _setup_legend(fig, cmap_params, label=hue)
     elif (
         isinstance(arr, xr.DataArray)
         and not geometry
         and not np.all(shapely.is_valid_input(arr))
     ):
-        _setup_colorbar(fig, cmap_params, label=label_from_attrs(arr))
+        _setup_legend(fig, cmap_params, label=label_from_attrs(arr))
 
     return fig, axs
diff --git a/xvec/tests/baseline_images/test_plotting/1d.png b/xvec/tests/baseline_images/test_plotting/1d.png
new file mode 100644
index 0000000..ec9fea4
Binary files /dev/null and b/xvec/tests/baseline_images/test_plotting/1d.png differ
diff --git a/xvec/tests/baseline_images/test_plotting/categorical.png b/xvec/tests/baseline_images/test_plotting/categorical.png
new file mode 100644
index 0000000..31237dd
Binary files /dev/null and b/xvec/tests/baseline_images/test_plotting/categorical.png differ
diff --git a/xvec/tests/test_plotting.py b/xvec/tests/test_plotting.py
index 5f34473..1a375d9 100644
--- a/xvec/tests/test_plotting.py
+++ b/xvec/tests/test_plotting.py
@@ -70,6 +70,14 @@ def test_col_row(aggregated):
     assert ax[0][1].get_ylabel() == "level = 200"
 
 
+@image_comparison(baseline_images=["1d"], extensions=["png"], style=[])
+def test_1d(aggregated):
+    f, ax = aggregated.z.sel(level=200, month=1).xvec.plot()
+
+    assert ax.get_xlabel() == "Geodetic longitude\n[degree]"
+    assert ax.get_ylabel() == "Geodetic latitude\n[degree]"
+
+
 @image_comparison(baseline_images=["var_geom"], extensions=["png"], style=[])
 def test_var_geom(glaciers):
     f, ax = glaciers.geometry.xvec.plot(col="year")
@@ -123,3 +131,19 @@ def test_geom_switching(glaciers):
     f, ax = glaciers_w_sum.xvec.plot(geometry="summary_geometry")
     assert ax.get_xlabel() == "Easting\n[metre]"
     assert ax.get_ylabel() == "Northing\n[metre]"
+
+
+@image_comparison(
+    baseline_images=["categorical"],
+    extensions=["png"],
+    style=[],
+    savefig_kwarg=dict(bbox_inches="tight"),
+)
+def test_categorical(glaciers):
+    f, ax = glaciers.xvec.plot(col="year", geometry="geometry", hue="name")
+
+    assert ax.shape == (1, 3)
+    ax0 = ax[0][0]
+    assert ax0.get_xlabel() == "Easting\n[metre]"
+    assert ax0.get_ylabel() == "Northing\n[metre]"
+    assert ax0.get_title() == "year = 1936.0"