update

Author: jreback

doc/source/missing_data.rst

@@ -192,7 +192,7 @@ Sum/Prod of Empties/Nans
    This behavior is now standard as of v0.21.0; previously sum/prod would give different
    results if the ``bottleneck`` package was installed. See the :ref:`here <whatsnew_0210.api_breaking.bottleneck>`.
 
-If summing a ``DataFrame``, a ``Series`` of all-``NaN``.
+With ``sum`` or ``prod`` on an empty or all-``NaN`` ``Series``, or columns of a ``DataFrame``, the result will be all-``NaN``.
 
 .. ipython:: python
 
@@ -208,7 +208,7 @@ Summing of an empty ``Series``
 
 .. warning::
 
-   These behaviors differ from the default in ``numpy`` which does not generally propagate NaNs
+   These behaviors differ from the default in ``numpy`` where an empty sum returns zero.
 
    .. ipython:: python
 

doc/source/whatsnew/v0.21.0.txt

@@ -421,9 +421,7 @@ Sum/Prod of all-NaN Series/DataFrames is now consistently NaN
 The behavior of ``sum`` and ``prod`` on all-NaN Series/DataFrames is now consistent and no longer depends on
 whether `bottleneck <http://berkeleyanalytics.com/bottleneck>`__ is installed. (:issue:`9422`, :issue:`15507`).
 
-This now will *always* preserve information. You will get back a ``NaN``, indicating missing values in that Series,
-or if summing a ``DataFrame``, a ``Series`` of all-``NaN``. See the :ref:`docs <missing_data.numeric_sum>`.
-
+With ``sum`` or ``prod`` on an empty or all-``NaN`` ``Series``, or columns of a ``DataFrame``, the result will be all-``NaN``. See the :ref:`docs <missing_data.numeric_sum>`.
 
 .. ipython:: python
 

pandas/core/generic.py

@@ -6990,7 +6990,7 @@ def _doc_parms(cls):
 ----------
 axis : %(axis_descr)s
 skipna : boolean, default True
-    Exclude NA/null values. If an entire row/column is NA, the result
+    Exclude NA/null values. If an entire row/column is NA or empty, the result
     will be NA
 level : int or level name, default None
     If the axis is a MultiIndex (hierarchical), count along a