Fix some scatter plot issues (#7167)

* User markersize for scatter plots.

* fix .values_unique not returning same values as .values

* fix typing issues in _Normalize

* fix typing issues with None with hueplt_norms

* fix typing issues with None hueplt_norm

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: Illviljan

xarray/plot/dataarray_plot.py

@@ -10,6 +10,7 @@
     Iterable,
     Literal,
     MutableMapping,
+    cast,
     overload,
 )
 
@@ -925,7 +926,7 @@ def newplotfunc(
 
         _is_facetgrid = kwargs.pop("_is_facetgrid", False)
 
-        if markersize is not None:
+        if plotfunc.__name__ == "scatter":
             size_ = markersize
             size_r = _MARKERSIZE_RANGE
         else:
@@ -960,7 +961,7 @@ def newplotfunc(
 
             cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
                 plotfunc,
-                hueplt_norm.values.data,
+                cast("DataArray", hueplt_norm.values).data,
                 **locals(),
             )
 
@@ -1013,13 +1014,7 @@ def newplotfunc(
             )
 
         if add_legend_:
-            if plotfunc.__name__ == "hist":
-                ax.legend(
-                    handles=primitive[-1],
-                    labels=list(hueplt_norm.values.to_numpy()),
-                    title=label_from_attrs(hueplt_norm.data),
-                )
-            elif plotfunc.__name__ in ["scatter", "line"]:
+            if plotfunc.__name__ in ["scatter", "line"]:
                 _add_legend(
                     hueplt_norm
                     if add_legend or not add_colorbar_
@@ -1030,11 +1025,26 @@ def newplotfunc(
                     plotfunc=plotfunc.__name__,
                 )
             else:
-                ax.legend(
-                    handles=primitive,
-                    labels=list(hueplt_norm.values.to_numpy()),
-                    title=label_from_attrs(hueplt_norm.data),
-                )
+                hueplt_norm_values: list[np.ndarray | None]
+                if hueplt_norm.data is not None:
+                    hueplt_norm_values = list(
+                        cast("DataArray", hueplt_norm.data).to_numpy()
+                    )
+                else:
+                    hueplt_norm_values = [hueplt_norm.data]
+
+                if plotfunc.__name__ == "hist":
+                    ax.legend(
+                        handles=primitive[-1],
+                        labels=hueplt_norm_values,
+                        title=label_from_attrs(hueplt_norm.data),
+                    )
+                else:
+                    ax.legend(
+                        handles=primitive,
+                        labels=hueplt_norm_values,
+                        title=label_from_attrs(hueplt_norm.data),
+                    )
 
         _update_axes(
             ax, xincrease, yincrease, xscale, yscale, xticks, yticks, xlim, ylim

xarray/plot/facetgrid.py

@@ -12,6 +12,7 @@
     Iterable,
     Literal,
     TypeVar,
+    cast,
 )
 
 import numpy as np
@@ -41,6 +42,9 @@
     from matplotlib.quiver import QuiverKey
     from matplotlib.text import Annotation
 
+    from ..core.dataarray import DataArray
+
+
 # Overrides axes.labelsize, xtick.major.size, ytick.major.size
 # from mpl.rcParams
 _FONTSIZE = "small"
@@ -402,18 +406,24 @@ def map_plot1d(
         hueplt_norm = _Normalize(hueplt)
         self._hue_var = hueplt
         cbar_kwargs = kwargs.pop("cbar_kwargs", {})
-        if not hueplt_norm.data_is_numeric:
-            # TODO: Ticks seems a little too hardcoded, since it will always
-            # show all the values. But maybe it's ok, since plotting hundreds
-            # of categorical data isn't that meaningful anyway.
-            cbar_kwargs.update(format=hueplt_norm.format, ticks=hueplt_norm.ticks)
-            kwargs.update(levels=hueplt_norm.levels)
-        if "label" not in cbar_kwargs:
-            cbar_kwargs["label"] = label_from_attrs(hueplt_norm.data)
-        cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
-            func, hueplt_norm.values.to_numpy(), cbar_kwargs=cbar_kwargs, **kwargs
-        )
-        self._cmap_extend = cmap_params.get("extend")
+
+        if hueplt_norm.data is not None:
+            if not hueplt_norm.data_is_numeric:
+                # TODO: Ticks seems a little too hardcoded, since it will always
+                # show all the values. But maybe it's ok, since plotting hundreds
+                # of categorical data isn't that meaningful anyway.
+                cbar_kwargs.update(format=hueplt_norm.format, ticks=hueplt_norm.ticks)
+                kwargs.update(levels=hueplt_norm.levels)
+
+            cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
+                func,
+                cast("DataArray", hueplt_norm.values).data,
+                cbar_kwargs=cbar_kwargs,
+                **kwargs,
+            )
+            self._cmap_extend = cmap_params.get("extend")
+        else:
+            cmap_params = {}
 
         # Handle sizes:
         _size_r = _MARKERSIZE_RANGE if func.__name__ == "scatter" else _LINEWIDTH_RANGE
@@ -513,6 +523,9 @@ def map_plot1d(
 
         if add_colorbar:
             # Colorbar is after legend so it correctly fits the plot:
+            if "label" not in cbar_kwargs:
+                cbar_kwargs["label"] = label_from_attrs(hueplt_norm.data)
+
             self.add_colorbar(**cbar_kwargs)
 
         return self