diff --git a/hvplot/converter.py b/hvplot/converter.py
index 00e31fe12..b1b03f80d 100644
--- a/hvplot/converter.py
+++ b/hvplot/converter.py
@@ -59,6 +59,7 @@
     is_cudf,
     is_streamz,
     is_ibis,
+    is_xvec,
     is_xarray,
     is_xarray_dataarray,
     process_crs,
@@ -1048,6 +1049,22 @@ def _process_data(
         if col is not None:
             grid.append(col)
         streaming = False
+
+        if is_xvec(data):
+            import xvec  # noqa: F401
+
+            geom_coords = list(data.xvec.geom_coords)
+            if len(geom_coords) > 1:
+                param.main.param.warning(
+                    f'Only the first geometry coord will be rendered: {geom_coords[0]!r}. The '
+                    f"others are 'flattened' in groupby: {geom_coords[1:]}"
+                )
+                data = data.drop_vars(geom_coords[1:])
+            if groupby is None:
+                groupby = [dim for dim in data.dims if dim != geom_coords[0]]
+            data = data.xvec.to_geodataframe()
+            self.source_data = data
+
         if is_geodataframe(data):
             datatype = 'geopandas' if hasattr(data, 'geom_type') else 'spatialpandas'
             self.data = data
diff --git a/hvplot/util.py b/hvplot/util.py
index 75f1df016..9eeb4187c 100644
--- a/hvplot/util.py
+++ b/hvplot/util.py
@@ -430,6 +430,14 @@ def is_streamz(data):
     return sdf and isinstance(data, (sdf.DataFrame, sdf.Series, sdf.DataFrames, sdf.Seriess))
 
 
+def is_xvec(data):
+    if not hasattr(data, 'xvec'):
+        return False
+    import xvec  # noqa
+
+    return len(data.xvec.geom_coords) > 0
+
+
 def is_xarray(data):
     if not check_library(data, 'xarray'):
         return False
@@ -482,7 +490,18 @@ def is_geodataframe(data):
 
 
 def process_xarray(
-    data, x, y, by, groupby, use_dask, persist, gridded, label, value_label, other_dims, kind=None
+    data,
+    x,
+    y,
+    by,
+    groupby,
+    use_dask,
+    persist,
+    gridded,
+    label,
+    value_label,
+    other_dims,
+    kind=None,
 ):
     import xarray as xr
 
@@ -509,6 +528,7 @@ def process_xarray(
 
     data_vars = list(dataset.data_vars)
     ignore = (by or []) + (groupby or [])
+
     dims = [c for c in dataset.coords if dataset[c].shape != () and c not in ignore][::-1]
     index_dims = [d for d in dims if d in dataset.indexes]
 
@@ -565,6 +585,7 @@ def process_xarray(
 
         if groupby is None:
             groupby = [c for c in leftover_dims if c not in (by or [])]
+
     return data, x, y, by, groupby