ENH-19629: Adding numpy nansun/nanmean, etc etc to _cython_table

doc/source/whatsnew/v0.23.0.txt

@@ -856,7 +856,7 @@ Numeric
 - Bug in :class:`DataFrame` flex arithmetic (e.g. ``df.add(other, fill_value=foo)``) with a ``fill_value`` other than ``None`` failed to raise ``NotImplementedError`` in corner cases where either the frame or ``other`` has length zero (:issue:`19522`)
 - Multiplication and division of numeric-dtyped :class:`Index` objects with timedelta-like scalars returns ``TimedeltaIndex`` instead of raising ``TypeError`` (:issue:`19333`)
 - Bug where ``NaN`` was returned instead of 0 by :func:`Series.pct_change` and :func:`DataFrame.pct_change` when ``fill_method`` is not ``None`` (provided) (:issue:`19873`)
-
+- :meth:`~DataFrame.agg` now correctly handles numpy NaN-aware methods like :meth:`numpy.nansum` (:issue:`19629`)
 
 Indexing
 ^^^^^^^^

pandas/core/base.py

@@ -21,7 +21,7 @@
 from pandas.core import common as com, algorithms
 import pandas.core.nanops as nanops
 import pandas._libs.lib as lib
-from pandas.compat.numpy import function as nv
+from pandas.compat.numpy import function as nv, _np_version_under1p10
 from pandas.compat import PYPY
 from pandas.util._decorators import (Appender, cache_readonly,
                                      deprecate_kwarg, Substitution)
@@ -188,17 +188,29 @@ class SelectionMixin(object):
         builtins.max: 'max',
         builtins.min: 'min',
         np.sum: 'sum',
+        np.nansum: 'sum',
         np.mean: 'mean',
+        np.nanmean: 'mean',
         np.prod: 'prod',
         np.std: 'std',
+        np.nanstd: 'std',
         np.var: 'var',
+        np.nanvar: 'var',
         np.median: 'median',
+        np.nanmedian: 'median',
         np.max: 'max',
+        np.nanmax: 'max',
         np.min: 'min',
+        np.nanmin: 'min',
         np.cumprod: 'cumprod',
-        np.cumsum: 'cumsum'
+        np.nancumprod: 'cumprod',
+        np.cumsum: 'cumsum',
+        np.nancumsum: 'cumsum'
     }
 
+    if not _np_version_under1p10:
+        _cython_table[np.nanprod] = 'prod'
+
     @property
     def _selection_name(self):
         """

pandas/tests/test_nanops.py

@@ -1005,6 +1005,39 @@ def prng(self):
         return np.random.RandomState(1234)
 
 
+class TestNumpyNaNFunctions(object):
+
+    # xref GH 19629
+    def setup_method(self, method):
+        self.test_series = pd.Series([1, 2, 3, 4, 5, 6])
+        self.test_df = pd.DataFrame([[1, 2, 3], [4, 5, 6]])
+
+    def compare_method_output(self, data, method, nan_method):
+        tm.assert_almost_equal(data.agg(method),
+                               data.agg(nan_method),
+                               check_exact=True)
+
+    @pytest.mark.parametrize("standard, nan_method", [
+        (np.sum, np.nansum),
+        (np.mean, np.nanmean),
+        (np.std, np.nanstd),
+        (np.var, np.nanvar),
+        (np.median, np.nanmedian),
+        (np.max, np.nanmax),
+        (np.min, np.nanmin),
+        (np.cumprod, np.nancumprod),
+        (np.cumsum, np.nancumsum)
+    ])
+    def test_np_nan_functions(self, standard, nan_method):
+        self.compare_method_output(self.test_series, standard, nan_method)
+        self.compare_method_output(self.test_df, standard, nan_method)
+
+    @td.skip_if_no("numpy", min_version="1.10.0")
+    def test_np_nanprod(self):
+        self.compare_method_output(self.test_series, np.prod, np.nanprod)
+        self.compare_method_output(self.test_df, np.prod, np.nanprod)
+
+
 def test_use_bottleneck():
 
     if nanops._BOTTLENECK_INSTALLED: