ENH: fill_value argument for shift

pandas/core/frame.py

@@ -2827,9 +2827,9 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                                   downcast=downcast, **kwargs)
 
     @Appender(_shared_docs['shift'] % _shared_doc_kwargs)
-    def shift(self, periods=1, freq=None, axis=0):
+    def shift(self, periods=1, freq=None, axis=0, fill_value=np.nan):
         return super(DataFrame, self).shift(periods=periods, freq=freq,
-                                            axis=axis)
+                                            axis=axis, fill_value=fill_value)
 
     def set_index(self, keys, drop=True, append=False, inplace=False,
                   verify_integrity=False):

pandas/core/generic.py

@@ -5032,13 +5032,14 @@ def mask(self, cond, other=np.nan, inplace=False, axis=None, level=None,
     """)
 
     @Appender(_shared_docs['shift'] % _shared_doc_kwargs)
-    def shift(self, periods=1, freq=None, axis=0):
+    def shift(self, periods=1, freq=None, axis=0, fill_value=np.nan):
         if periods == 0:
             return self
 
         block_axis = self._get_block_manager_axis(axis)
         if freq is None:
-            new_data = self._data.shift(periods=periods, axis=block_axis)
+            new_data = self._data.shift(periods=periods, axis=block_axis,
+                                        fill_value=fill_value)
         else:
             return self.tshift(periods, freq)
 

pandas/core/internals.py

@@ -1060,12 +1060,13 @@ def diff(self, n, axis=1, mgr=None):
         new_values = algos.diff(self.values, n, axis=axis)
         return [self.make_block(values=new_values, fastpath=True)]
 
-    def shift(self, periods, axis=0, mgr=None):
+    def shift(self, periods, axis=0, fill_value=np.nan, mgr=None):
         """ shift the block by periods, possibly upcast """
 
         # convert integer to float if necessary. need to do a lot more than
         # that, handle boolean etc also
-        new_values, fill_value = _maybe_upcast(self.values)
+        new_values, fill_value = _maybe_upcast(self.values,
+                                               fill_value=fill_value)
 
         # make sure array sent to np.roll is c_contiguous
         f_ordered = new_values.flags.f_contiguous

pandas/core/series.py

@@ -2382,8 +2382,9 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                                           **kwargs)
 
     @Appender(generic._shared_docs['shift'] % _shared_doc_kwargs)
-    def shift(self, periods=1, freq=None, axis=0):
-        return super(Series, self).shift(periods=periods, freq=freq, axis=axis)
+    def shift(self, periods=1, freq=None, axis=0, fill_value=np.nan):
+        return super(Series, self).shift(periods=periods, freq=freq, axis=axis,
+                                         fill_value=fill_value)
 
     def reindex_axis(self, labels, axis=0, **kwargs):
         """ for compatibility with higher dims """