Use .to_numpy() for quantified facetgrids

xarray/plot/facetgrid.py

@@ -175,11 +175,11 @@ def __init__(
         )
 
         # Set up the lists of names for the row and column facet variables
-        col_names = list(data[col].values) if col else []
-        row_names = list(data[row].values) if row else []
+        col_names = list(data[col].to_numpy()) if col else []
+        row_names = list(data[row].to_numpy()) if row else []
 
         if single_group:
-            full = [{single_group: x} for x in data[single_group].values]
+            full = [{single_group: x} for x in data[single_group].to_numpy()]
             empty = [None for x in range(nrow * ncol - len(full))]
             name_dicts = full + empty
         else:
@@ -253,7 +253,7 @@ def map_dataarray(self, func, x, y, **kwargs):
             raise ValueError("cbar_ax not supported by FacetGrid.")
 
         cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
-            func, self.data.values, **kwargs
+            func, self.data.to_numpy(), **kwargs
         )
 
         self._cmap_extend = cmap_params.get("extend")
@@ -349,7 +349,7 @@ def map_dataset(
 
         if hue and meta_data["hue_style"] == "continuous":
             cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
-                func, self.data[hue].values, **kwargs
+                func, self.data[hue].to_numpy(), **kwargs
             )
             kwargs["meta_data"]["cmap_params"] = cmap_params
             kwargs["meta_data"]["cbar_kwargs"] = cbar_kwargs
@@ -425,7 +425,7 @@ def _adjust_fig_for_guide(self, guide):
     def add_legend(self, **kwargs):
         self.figlegend = self.fig.legend(
             handles=self._mappables[-1],
-            labels=list(self._hue_var.values),
+            labels=list(self._hue_var.to_numpy()),
             title=self._hue_label,
             loc="center right",
             **kwargs,
@@ -625,7 +625,7 @@ def map(self, func, *args, **kwargs):
             if namedict is not None:
                 data = self.data.loc[namedict]
                 plt.sca(ax)
-                innerargs = [data[a].values for a in args]
+                innerargs = [data[a].to_numpy() for a in args]
                 maybe_mappable = func(*innerargs, **kwargs)
                 # TODO: better way to verify that an artist is mappable?
                 # https://stackoverflow.com/questions/33023036/is-it-possible-to-detect-if-a-matplotlib-artist-is-a-mappable-suitable-for-use-w#33023522

xarray/plot/plot.py

@@ -1152,10 +1152,6 @@ def newplotfunc(
         else:
             dims = (yval.dims[0], xval.dims[0])
 
-        # better to pass the ndarrays directly to plotting functions
-        xval = xval.to_numpy()
-        yval = yval.to_numpy()
-
         # May need to transpose for correct x, y labels
         # xlab may be the name of a coord, we have to check for dim names
         if imshow_rgb:
@@ -1168,8 +1164,13 @@ def newplotfunc(
         if dims != darray.dims:
             darray = darray.transpose(*dims, transpose_coords=True)
 
+        # better to pass the ndarrays directly to plotting functions
+        xval = xval.to_numpy()
+        yval = yval.to_numpy()
+        zarray = darray.as_numpy()
+
         # Pass the data as a masked ndarray too
-        zval = darray.to_masked_array(copy=False)
+        zval = zarray.to_masked_array(copy=False)
 
         # Replace pd.Intervals if contained in xval or yval.
         xplt, xlab_extra = _resolve_intervals_2dplot(xval, plotfunc.__name__)