proper fix.

xarray/plot/plot.py

@@ -672,16 +672,22 @@ def newplotfunc(
 
         # check if we need to broadcast one dimension
         if xval.ndim < yval.ndim:
+            dims = darray[ylab].dims
             if xval.shape[0] == yval.shape[0]:
                 xval = np.broadcast_to(xval[:, np.newaxis], yval.shape)
             else:
                 xval = np.broadcast_to(xval[np.newaxis, :], yval.shape)
 
         elif yval.ndim < xval.ndim:
+            dims = darray[xlab].dims
             if yval.shape[0] == xval.shape[0]:
                 yval = np.broadcast_to(yval[:, np.newaxis], xval.shape)
             else:
                 yval = np.broadcast_to(yval[np.newaxis, :], xval.shape)
+        elif xval.ndim == 2:
+            dims = darray[xlab].dims
+        else:
+            dims = (darray[ylab].dims[0], darray[xlab].dims[0])
 
         # May need to transpose for correct x, y labels
         # xlab may be the name of a coord, we have to check for dim names
@@ -691,10 +697,9 @@ def newplotfunc(
             # we transpose to (y, x, color) to make this work.
             yx_dims = (ylab, xlab)
             dims = yx_dims + tuple(d for d in darray.dims if d not in yx_dims)
-            if dims != darray.dims:
-                darray = darray.transpose(*dims, transpose_coords=True)
-        elif darray[xlab].dims[-1] == darray.dims[0]:
-            darray = darray.transpose(transpose_coords=True)
+
+        if dims != darray.dims:
+            darray = darray.transpose(*dims, transpose_coords=True)
 
         # Pass the data as a masked ndarray too
         zval = darray.to_masked_array(copy=False)

xarray/tests/test_plot.py

@@ -2168,7 +2168,13 @@ def test_plot_transposed_nondim_coord(plotfunc):
     getattr(da.plot, plotfunc)(x="zt", y="x")
 
 
-def test_plot_transposes_properly():
+@requires_matplotlib
+@pytest.mark.parametrize("plotfunc", ["pcolormesh", "imshow"])
+def test_plot_transposes_properly(plotfunc):
+    # test that we aren't mistakenly transposing when the 2 dimensions have equal sizes.
     da = xr.DataArray([np.sin(2 * np.pi / 10 * np.arange(10))] * 10, dims=("y", "x"))
-    hdl = da.plot(x="x", y="y")
-    assert np.all(hdl.get_array() == da.to_masked_array().ravel())
+    hdl = getattr(da.plot, plotfunc)(x="x", y="y")
+    # get_array doesn't work for contour, contourf. It returns the colormap intervals.
+    # pcolormesh returns 1D array but imshow returns a 2D array so it is necessary
+    # to ravel() on the LHS
+    assert np.all(hdl.get_array().ravel() == da.to_masked_array().ravel())