diff --git a/python/damask/table.py b/python/damask/table.py
index 7d9e65961..bb195122d 100644
--- a/python/damask/table.py
+++ b/python/damask/table.py
@@ -6,40 +6,40 @@ import numpy as np
 class Table():
     """Store spreadsheet-like data."""
   
-    def __init__(self,array,headings,comments=None):
+    def __init__(self,data,shapes,comments=None):
         """
-        New spreadsheet data.
+        New spreadsheet.
         
         Parameters
         ----------
-        array : numpy.ndarray
+        data : numpy.ndarray
             Data.
-        headings : dict
-            Column headings. Labels as keys and shape as tuple. Example 'F':(3,3) for a deformation gradient. 
+        shapes : dict with str:tuple pairs
+            Shapes of the columns. Example 'F':(3,3) for a deformation gradient. 
         comments : iterable of str, optional
-            Additional, human-readable information
+            Additional, human-readable information.
         
         """
-        self.data = pd.DataFrame(data=array)
+        self.data = pd.DataFrame(data=data)
 
-        d = {}
+        labels = {}
         i = 0
-        for label in headings:
-            for components in range(np.prod(headings[label])):
-                d[i] = label
+        for label in shapes.keys():
+            for components in range(np.prod(shapes[label])):
+                labels[i] = label
                 i+=1
 
         if i != self.data.shape[1]:
-            raise IndexError('Mismatch between array shape and headings')
+            raise IndexError('Shape mismatch between shapes and data')
 
-        self.data.rename(columns=d,inplace=True)
+        self.data.rename(columns=labels,inplace=True)
 
         if comments is None:
             self.comments = []
         else:
             self.comments = [c for c in comments]
 
-        self.headings  = headings
+        self.shapes = shapes
 
     @staticmethod
     def from_ASCII(fname):
@@ -47,8 +47,8 @@ class Table():
         Create table from ASCII file.
 
         The first line needs to indicate the number of subsequent header lines as 'n header'.
-        Vector data labels are indicated by '1_v, 2_v, ..., n_v'.
-        Tensor data labels are indicated by '3x3:1_T, 3x3:2_T, ..., 3x3:9_T'.
+        Vector data column labels are indicated by '1_v, 2_v, ..., n_v'.
+        Tensor data column labels are indicated by '3x3:1_T, 3x3:2_T, ..., 3x3:9_T'.
 
         Parameters
         ----------
@@ -69,20 +69,20 @@ class Table():
         comments = [f.readline()[:-1] for i in range(header-1)]
         labels   = f.readline().split()
        
-        headings = {}
+        shapes = {}
         for label in labels:
             tensor_column = re.search(r'[0-9,x]*?:[0-9]*?_',label)
             if tensor_column:
                 my_shape = tensor_column.group().split(':',1)[0].split('x')
-                headings[label.split('_',1)[1]] = tuple([int(d) for d in my_shape])
+                shapes[label.split('_',1)[1]] = tuple([int(d) for d in my_shape])
             else:
                 vector_column = re.match(r'[0-9]*?_',label)
                 if vector_column:
-                    headings[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
+                    shapes[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
                 else:
-                    headings[label]=(1,)
+                    shapes[label]=(1,)
         
-        return Table(np.loadtxt(f),headings,comments)
+        return Table(np.loadtxt(f),shapes,comments)
 
     def get_array(self,label):
         """
@@ -98,7 +98,7 @@ class Table():
             idx,key = label.split('_',1)
             return self.data[key].to_numpy()[:,int(idx)-1]
         else: 
-            return self.data[label].to_numpy().reshape((-1,)+self.headings[label])
+            return self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
 
     def set_array(self,label,array,info):
         """
@@ -129,7 +129,7 @@ class Table():
 
     def get_labels(self):
         """Return the labels of all columns."""
-        return [label for label in self.headings]
+        return list(self.shapes.keys())
 
     def add_array(self,label,array,info):
         """
@@ -150,7 +150,7 @@ class Table():
         else:
             self.comments.append('{} {}: {}'.format(label,array.shape[1:],info))
         
-        self.headings[label] = array.shape[1:] if len(array.shape) > 1 else (1,)
+        self.shapes[label] = array.shape[1:] if len(array.shape) > 1 else (1,)
         size = np.prod(array.shape[1:],dtype=int) 
         new_data = pd.DataFrame(data=array.reshape(-1,size),
                                 columns=[label for l in range(size)])
@@ -167,15 +167,15 @@ class Table():
 
         """
         labels = []
-        for l in self.headings:
-            if(self.headings[l] == (1,)):
+        for l in self.shapes:
+            if(self.shapes[l] == (1,)):
                 labels.append('{}'.format(l))
-            elif(len(self.headings[l]) == 1):
+            elif(len(self.shapes[l]) == 1):
                 labels+=['{}_{}'.format(i+1,l)\
-                         for i in range(self.headings[l][0])]
+                         for i in range(self.shapes[l][0])]
             else:
-                labels+=['{}:{}_{}'.format('x'.join([str(d) for d in self.headings[l]]),i+1,l)\
-                               for i in range(np.prod(self.headings[l],dtype=int))]
+                labels+=['{}:{}_{}'.format('x'.join([str(d) for d in self.shapes[l]]),i+1,l)\
+                               for i in range(np.prod(self.shapes[l],dtype=int))]
 
         header = ['{} header'.format(len(self.comments)+1)]\
                + self.comments\