diff --git a/changelog/479.bugfix.rst b/changelog/479.bugfix.rst
new file mode 100644
index 00000000..19d1eb1e
--- /dev/null
+++ b/changelog/479.bugfix.rst
@@ -0,0 +1 @@
+Fix some small issues with `Dataset.__repr__`.
diff --git a/dkist/dataset/tests/test_dataset.py b/dkist/dataset/tests/test_dataset.py
index 90b8c577..e227f4a3 100644
--- a/dkist/dataset/tests/test_dataset.py
+++ b/dkist/dataset/tests/test_dataset.py
@@ -50,6 +50,14 @@ def test_repr(dataset, dataset_3d):
     r = repr(dataset_3d)
     assert str(dataset_3d.data) in r
 
+def test_repr_numpy(dataset):
+    # Do it the old way to support old ndcube
+    dataset._data = dataset.data.compute()
+    r = repr(dataset)
+    assert "numpy.ndarray" in r
+    assert f"{dataset.data.shape}" in r
+    assert f"{dataset.data.dtype}" in r
+
 
 @pytest.mark.accept_cli_dataset
 def test_wcs_roundtrip(dataset):
diff --git a/dkist/dataset/tests/test_tiled_dataset.py b/dkist/dataset/tests/test_tiled_dataset.py
index e72b8117..c01abd36 100644
--- a/dkist/dataset/tests/test_tiled_dataset.py
+++ b/dkist/dataset/tests/test_tiled_dataset.py
@@ -81,7 +81,7 @@ def test_tileddataset_plot(share_zscale):
     newtiles = []
     for tile in ds.flat:
         newtiles.append(tile.rebin((1, 8, 8), operation=np.sum))
-    ds = TiledDataset(np.array(newtiles).reshape(ds.shape), inventory=ds.inventory)
+    ds = TiledDataset(np.array(newtiles).reshape(ds.shape), inventory=newtiles[0].inventory)
     fig = plt.figure(figsize=(600, 800))
     ds.plot(0, share_zscale=share_zscale)
     return plt.gcf()
diff --git a/dkist/dataset/utils.py b/dkist/dataset/utils.py
index bab3e338..d29af480 100644
--- a/dkist/dataset/utils.py
+++ b/dkist/dataset/utils.py
@@ -11,6 +11,17 @@
 __all__ = ["dataset_info_str"]
 
 
+def get_array_repr(array):
+    """
+    Return a "repr-like" string for an array, without any values.
+
+    The objective of this function is primarily to provide a dask array like repr for numpy arrays.
+    """
+    if isinstance(array, np.ndarray):
+        return f"numpy.ndarray<shape={array.shape}, dtype={array.dtype}>"
+    return repr(array)
+
+
 def dataset_info_str(ds_in):
     # Check for an attribute that only appears on TiledDataset
     # Not using isinstance to avoid circular import
@@ -48,7 +59,7 @@ def dataset_info_str(ds_in):
         s += "\nThis "
     s += f"Dataset has {wcs.pixel_n_dim} pixel and {wcs.world_n_dim} world dimensions.\n\n"
 
-    s += f"The data are represented by a {type(ds.data)} object:\n{ds.data}\n\n"
+    s += f"The data are represented by a {type(ds.data)} object:\n{get_array_repr(ds.data)}\n\n"
 
     array_shape = wcs.array_shape or (0,)
     pixel_shape = wcs.pixel_shape or (None,) * wcs.pixel_n_dim
@@ -139,7 +150,7 @@ def _get_pp_matrix(wcs):
         world.insert(0, "")
     mstr = np.insert(mstr, 0, world, axis=1)
     widths = [np.max([len(a) for a in col]) for col in mstr.T]
-    mstr = np.insert(mstr, 2, ["-"*wid for wid in widths], axis=0)
+    mstr = np.insert(mstr, header.shape[0], ["-"*wid for wid in widths], axis=0)
     for i, col in enumerate(mstr.T):
         if i == 0:
             mstr[:, i] = np.char.rjust(col, widths[i])