save

dios/base.py

@@ -318,6 +318,7 @@ class _DiosBase:
 
     @property
     def columns(self):
+        """ The column labels of the DictOfSeries """
         return self._data.index
 
     @columns.setter
@@ -329,6 +330,10 @@ class _DiosBase:
 
     @property
     def itype(self):
+        """ The ``Itype`` of the DictOfSeries.
+
+        See :ref:`Itype documentation <doc_itype:Itype>` for more info.
+        """
         if self._itype == 'INFER':
             return None
         return self._itype
@@ -341,6 +346,10 @@ class _DiosBase:
 
     @property
     def cast_policy(self):
+        """ The policy to use for casting new columns if its initial itype does not fit.
+
+        See :ref:`Itype documentation <doc_itype:Itype>` for more info.
+        """
         return self._policy
 
     @cast_policy.setter
@@ -363,6 +372,47 @@ class _DiosBase:
 
     @property
     def empty(self):
+        """ Indicator whether DictOfSeries is empty.
+
+        Returns
+        -------
+        bool :
+            If DictOfSeries is empty, return True, if not return False.
+
+        See Also
+        --------
+        DictOfSeries.dropempty : drop empty columns
+        DictOfSeries.dropna : drop NAN's from a DictOfSeries
+        pandas.Series.dropna : drop NAN's from a Series
+
+        Notes
+        -----
+            If DictOfSeries contains only NaNs, it is still not considered empty. See the example below.
+            
+        Examples
+        --------
+        An example of an actual empty DictOfSeries.
+
+        >>> di_empty = DictOfSeries(columns=['A'])
+        >>> di_empty
+        Empty DictOfSeries
+        Columns: ['A']
+        >>> di_empty.empty
+        True
+        
+        If we only have NaNs in our DictOfSeries, it is not considered empty!
+        We will need to drop the NaNs to make the DictOfSeries empty:
+        
+        >>> di = pd.DictOfSeries({'A' : [np.nan]})
+        >>> di
+            A | 
+        ===== |
+        0 NaN |
+        >>> di.empty
+        False
+        >>> di.dropna().empty
+        True
+        """
         return len(self) == 0 or all(s.empty for s in self._data)
 
     def __iter__(self):
@@ -384,6 +434,22 @@ class _DiosBase:
         return self.copy(deep=True)
 
     def copy(self, deep=True):
+        """ Make a copy of this DictOfSeries' indices and data.
+
+        Parameters
+        ----------
+        deep : bool, default True
+            Make a deep copy, including a copy of the data and the indices.
+            With deep=False neither the indices nor the data are copied.
+
+        Returns
+        -------
+        copy : DictOfSeries
+
+        See Also
+        --------
+        pandas.DataFrame.copy
+        """
         if deep:
             data = pd.Series(dtype='O', index=self.columns)
             for c in self.columns:
@@ -479,6 +545,10 @@ class _DiosBase:
 
     @property
     def loc(self):
+        """ Location Indexer.
+
+        See :ref:`indexing docs <doc_indexing:Pandas-like indexing>`
+        """
         return _LocIndexer(self)
 
     @property

dox/doc_itype.md

+Itype
+=====
\ No newline at end of file

dox/index.rst

@@ -15,22 +15,26 @@ the class :class:`dios.DictOfSeries`. See
 
    dios.DictOfSeries <_api/dios.DictOfSeries>
 
-For some recipes and advanced usage see:
+Most magic happen in getting and setting elements.
+To select any combination from columns and rows,
+read the documentation about indexing:
 
 .. toctree::
 
-   indexingDocs
+   doc_indexing
 
 .. toctree::
 
-   cookbook
+   doc_cookbook
 
-For full module api documentation see:
+
+For implemented methods and module functions,
+respectively the full module api, see:
 
 .. toctree::
    :maxdepth: 2
 
-   _diosApi
+   dios_api
 
 or browse the Index..