BUG: Prevent abuse of kwargs in stat functions

Addresses issue #12301 by filtering `kwargs` argument in stat
functions to prevent the passage of clearly invalid arguments while at
the same time maintaining compatibility with analogous `numpy`
functions.

Author: gfyoung <[email protected]>

Closes #12318 from gfyoung/kwarg_remover and squashes the following commits:

f9de80f [gfyoung] BUG: Prevent abuse of kwargs in stat functions

Author: gfyoung

doc/source/whatsnew/v0.18.0.txt

@@ -824,6 +824,8 @@ Other API Changes
 
 - As part of the new API for :ref:`window functions <whatsnew_0180.enhancements.moments>` and :ref:`resampling <whatsnew_0180.breaking.resample>`, aggregation functions have been clarified, raising more informative error messages on invalid aggregations. (:issue:`9052`). A full set of examples are presented in :ref:`groupby <groupby.aggregation>`.
 
+- Statistical functions for ``NDFrame`` objects will now raise if non-numpy-compatible arguments are passed in for ``**kwargs`` (:issue:`12301`)
+
 .. _whatsnew_0180.deprecations:
 
 Deprecations

pandas/core/generic.py

@@ -5207,12 +5207,29 @@ def _doc_parms(cls):
 %(outname)s : %(name1)s\n"""
 
 
+def _validate_kwargs(fname, kwargs, *compat_args):
+    """
+    Checks whether parameters passed to the
+    **kwargs argument in a 'stat' function 'fname'
+    are valid parameters as specified in *compat_args
+
+    """
+    list(map(kwargs.__delitem__, filter(
+        kwargs.__contains__, compat_args)))
+    if kwargs:
+        bad_arg = list(kwargs)[0]  # first 'key' element
+        raise TypeError(("{fname}() got an unexpected "
+                         "keyword argument '{arg}'".
+                         format(fname=fname, arg=bad_arg)))
+
+
 def _make_stat_function(name, name1, name2, axis_descr, desc, f):
     @Substitution(outname=name, desc=desc, name1=name1, name2=name2,
                   axis_descr=axis_descr)
     @Appender(_num_doc)
     def stat_func(self, axis=None, skipna=None, level=None, numeric_only=None,
                   **kwargs):
+        _validate_kwargs(name, kwargs, 'out', 'dtype')
         if skipna is None:
             skipna = True
         if axis is None:
@@ -5233,6 +5250,7 @@ def _make_stat_function_ddof(name, name1, name2, axis_descr, desc, f):
     @Appender(_num_ddof_doc)
     def stat_func(self, axis=None, skipna=None, level=None, ddof=1,
                   numeric_only=None, **kwargs):
+        _validate_kwargs(name, kwargs, 'out', 'dtype')
         if skipna is None:
             skipna = True
         if axis is None:
@@ -5254,6 +5272,7 @@ def _make_cum_function(name, name1, name2, axis_descr, desc, accum_func,
     @Appender("Return cumulative {0} over requested axis.".format(name) +
               _cnum_doc)
     def func(self, axis=None, dtype=None, out=None, skipna=True, **kwargs):
+        _validate_kwargs(name, kwargs, 'out', 'dtype')
         if axis is None:
             axis = self._stat_axis_number
         else:
@@ -5288,6 +5307,7 @@ def _make_logical_function(name, name1, name2, axis_descr, desc, f):
     @Appender(_bool_doc)
     def logical_func(self, axis=None, bool_only=None, skipna=None, level=None,
                      **kwargs):
+        _validate_kwargs(name, kwargs, 'out', 'dtype')
         if skipna is None:
             skipna = True
         if axis is None:

pandas/tests/test_generic.py

@@ -16,12 +16,14 @@
 
 from pandas.compat import range, zip
 from pandas import compat
-from pandas.util.testing import (assert_series_equal,
+from pandas.util.testing import (assertRaisesRegexp,
+                                 assert_series_equal,
                                  assert_frame_equal,
                                  assert_panel_equal,
                                  assert_panel4d_equal,
                                  assert_almost_equal,
                                  assert_equal)
+
 import pandas.util.testing as tm
 
 
@@ -483,8 +485,6 @@ def test_split_compat(self):
         self.assertTrue(len(np.array_split(o, 2)) == 2)
 
     def test_unexpected_keyword(self):  # GH8597
-        from pandas.util.testing import assertRaisesRegexp
-
         df = DataFrame(np.random.randn(5, 2), columns=['jim', 'joe'])
         ca = pd.Categorical([0, 0, 2, 2, 3, np.nan])
         ts = df['joe'].copy()
@@ -502,6 +502,20 @@ def test_unexpected_keyword(self):  # GH8597
         with assertRaisesRegexp(TypeError, 'unexpected keyword'):
             ts.fillna(0, in_place=True)
 
+    # See gh-12301
+    def test_stat_unexpected_keyword(self):
+        obj = self._construct(5)
+        starwars = 'Star Wars'
+
+        with assertRaisesRegexp(TypeError, 'unexpected keyword'):
+            obj.max(epic=starwars)  # stat_function
+        with assertRaisesRegexp(TypeError, 'unexpected keyword'):
+            obj.var(epic=starwars)  # stat_function_ddof
+        with assertRaisesRegexp(TypeError, 'unexpected keyword'):
+            obj.sum(epic=starwars)  # cum_function
+        with assertRaisesRegexp(TypeError, 'unexpected keyword'):
+            obj.any(epic=starwars)  # logical_function
+
 
 class TestSeries(tm.TestCase, Generic):
     _typ = Series