add np.nan* funcs to cython_table

Author: topper-123

Diff for: doc/source/whatsnew/v0.24.0.txt

@@ -478,6 +478,7 @@ Numeric
 - Bug in :meth:`DataFrame.agg`, :meth:`DataFrame.transform` and :meth:`DataFrame.apply` where,
   when supplied with a list of functions and ``axis=1`` (e.g. ``df.apply(['sum', 'mean'], axis=1)``),
   a ``TypeError`` was wrongly raised. For all three methods such calculation are now done correctly. (:issue:`16679`).
+- :meth:`Series.agg` can now handle numpy NaN-aware methods like :func:`numpy.nansum` (:issue:`19629`)
 -
 
 Strings

Diff for: pandas/core/base.py

@@ -22,7 +22,8 @@
 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,
+                                 _np_version_under1p12)
 from pandas.compat import PYPY
 from pandas.util._decorators import (Appender, cache_readonly,
                                      deprecate_kwarg, Substitution)
@@ -184,24 +185,39 @@ class SelectionMixin(object):
         builtins.max: np.max,
         builtins.min: np.min
     }
+
     _cython_table = {
         builtins.sum: 'sum',
         builtins.max: 'max',
         builtins.min: 'min',
         np.all: 'all',
         np.any: 'any',
         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.cumsum: 'cumsum',
     }
 
+    if not _np_version_under1p10:
+        _cython_table[np.nanprod] = 'prod'
+
+    if not _np_version_under1p12:
+        _cython_table[np.nancumprod] = 'cumprod'
+        _cython_table[np.nancumsum] = 'cumsum'
+
     @property
     def _selection_name(self):
         """