DOC: have software names appear in includes through substitution

Author: afeld

doc/source/getting_started/comparison/comparison_with_sas.rst

@@ -461,6 +461,8 @@ For example, in SAS you could do this to filter missing values.
 
 .. include:: includes/missing.rst
 
+.. |program| replace:: SAS
+
 
 GroupBy
 -------

doc/source/getting_started/comparison/comparison_with_stata.rst

@@ -448,6 +448,8 @@ For example, in Stata you could do this to filter missing values.
 
 .. include:: includes/missing.rst
 
+.. |program| replace:: Stata
+
 
 GroupBy
 -------

doc/source/getting_started/comparison/includes/missing.rst

@@ -6,11 +6,10 @@ should be used for comparisons.
    outer_join[pd.isna(outer_join["value_x"])]
    outer_join[pd.notna(outer_join["value_x"])]
 
-pandas also provides a variety of methods to work with missing data -- some of
-which would be challenging to express in Stata. For example, there are methods to
-drop all rows with any missing values, replacing missing values with a specified
-value, like the mean, or forward filling from previous rows. See the
-:ref:`missing data documentation<missing_data>` for more.
+pandas also provides a variety of methods to work with missing data -- some of which would be
+challenging to express in |program|. For example, there are methods to drop all rows with any
+missing values, replacing missing values with a specified value, like the mean, or forward filling
+from previous rows. See the :ref:`missing data documentation<missing_data>` for more.
 
 .. ipython:: python
 

doc/source/getting_started/comparison/includes/missing_intro.rst

@@ -1,6 +1,6 @@
-Both have a representation for missing data — pandas' is the special float value ``NaN`` (not a
-number).  Many of the semantics are the same; for example missing data propagates through numeric
-operations, and is ignored by default for aggregations.
+Both pandas and |program| have a representation for missing data — pandas' is the special float
+value ``NaN`` (not a number).  Many of the semantics are the same; for example missing data
+propagates through numeric operations, and is ignored by default for aggregations.
 
 .. ipython:: python