diff --git a/PRIVATE b/PRIVATE
index cdca8ab0c..a8bd47ad5 160000
--- a/PRIVATE
+++ b/PRIVATE
@@ -1 +1 @@
-Subproject commit cdca8ab0c14b637c18279e0ea236caa148d15e5e
+Subproject commit a8bd47ad55125b477e6c03277ee38ce3998a66ca
diff --git a/python/damask/_table.py b/python/damask/_table.py
index b42c18703..356e73730 100644
--- a/python/damask/_table.py
+++ b/python/damask/_table.py
@@ -12,18 +12,18 @@ class Table:
     """Manipulate multi-dimensional spreadsheet-like data."""
 
     def __init__(self,
-                 shapes: dict,
-                 data: np.ndarray,
+                 shapes: dict = {},
+                 data: np.ndarray = None,
                  comments: Union[str, Iterable[str]] = None):
         """
         New spreadsheet.
 
         Parameters
         ----------
-        shapes : dict with str:tuple pairs
-            Shapes of the data columns.
+        shapes : dict with str:tuple pairs, optional
+            Shapes of the data columns. Mandatory if 'data' is given.
             For instance, 'F':(3,3) for a deformation gradient, or 'r':(1,) for a scalar.
-        data : numpy.ndarray or pandas.DataFrame
+        data : numpy.ndarray or pandas.DataFrame, optional
             Data. Existing column labels of a pandas.DataFrame will be replaced.
         comments : str or iterable of str, optional
             Additional, human-readable information.
@@ -427,7 +427,7 @@ class Table:
             new = pd.DataFrame(data=data.reshape(-1,size),
                                columns=[label]*size,
                               )
-            new.index = dup.data.index
+            new.index = new.index if dup.data.index.empty else dup.data.index
             dup.data = pd.concat([dup.data,new],axis=1)
 
         return dup
diff --git a/python/tests/test_Table.py b/python/tests/test_Table.py
index e530abe58..5eb950817 100644
--- a/python/tests/test_Table.py
+++ b/python/tests/test_Table.py
@@ -38,6 +38,17 @@ class TestTable:
         d = default.get('F')
         assert np.allclose(d,1.0) and d.shape[1:] == (3,3)
 
+    def test_empty_init(self):
+        N = 3
+        D = dict(
+                 scal=np.arange(10),
+                 vctr=np.arange(10*N).reshape((10,N)),
+                )
+        t = Table()
+        for label,data in D.items():
+            t = t.set(label,data)
+        assert np.allclose(t.get('scal').flatten()*3,t.get('vctr')[:,0])
+
     def test_set(self,default):
         d = default.set('F',np.zeros((5,3,3)),'set to zero').get('F')
         assert np.allclose(d,0.0) and d.shape[1:] == (3,3)