WIP/ENH: add weights kw to numeric aggregation functions

pandas/compat/numpy/function.py

@@ -306,13 +306,16 @@ def validate_expanding_func(name, args, kwargs):
             raise UnsupportedFunctionCall(msg)
 
 
-def validate_groupby_func(name, args, kwargs):
+def validate_groupby_func(name, args, kwargs, allowed_kwargs=None):
     """
-    'args' and 'kwargs' should be empty because all of
+    'args' should be empty because all of
     their necessary parameters are explicitly listed in
     the function signature
     """
-    if len(args) + len(kwargs) > 0:
+    if allowed_kwargs:
+        kwargs = set(kwargs) - set(allowed_kwargs)
+
+    if len(args) or len(kwargs):
         raise UnsupportedFunctionCall((
             "numpy operations are not valid "
             "with groupby. Use .groupby(...)."

pandas/core/base.py

@@ -910,12 +910,18 @@ def hasnans(self):
         return isnull(self).any()
 
     def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, **kwds):
+                weights=None, filter_type=None, **kwds):
         """ perform the reduction type operation if we can """
         func = getattr(self, name, None)
         if func is None:
             raise TypeError("{klass} cannot perform the operation {op}".format(
                             klass=self.__class__.__name__, op=name))
+
+        if weights is not None:
+            from pandas.tools import weightby
+            _, weights = weightby.weightby(self, weights=weights, axis=axis)
+            kwds['weights'] = weights
+
         return func(**kwds)
 
     def value_counts(self, normalize=False, sort=True, ascending=False,

pandas/core/categorical.py

@@ -1747,7 +1747,7 @@ def _reverse_indexer(self):
 
     # reduction ops #
     def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, **kwds):
+                weights=None, filter_type=None, **kwds):
         """ perform the reduction type operation """
         func = getattr(self, name, None)
         if func is None:

pandas/core/frame.py

@@ -4894,10 +4894,15 @@ def _count_level(self, level, axis=0, numeric_only=False):
         else:
             return result
 
-    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, weights=None,
+                numeric_only=None, filter_type=None, **kwds):
         axis = self._get_axis_number(axis)
 
+        if weights is not None:
+            from pandas.tools import weightby
+            self, weights = weightby.weightby(self, weights=weights, axis=axis)
+            kwds['weights'] = weights
+
         def f(x):
             return op(x, axis=axis, skipna=skipna, **kwds)