diff --git a/doc/source/comparison_with_sas.rst b/doc/source/comparison_with_sas.rst
index 214667119f7e0..0354ad473544b 100644
--- a/doc/source/comparison_with_sas.rst
+++ b/doc/source/comparison_with_sas.rst
@@ -25,7 +25,7 @@ As is customary, we import pandas and NumPy as follows:
This is often used in interactive work (e.g. `Jupyter notebook
`_ or terminal) - the equivalent in SAS would be:
- .. code-block:: none
+ .. code-block:: sas
proc print data=df(obs=5);
run;
@@ -65,7 +65,7 @@ in the ``DATA`` step.
Every ``DataFrame`` and ``Series`` has an ``Index`` - which are labels on the
*rows* of the data. SAS does not have an exactly analogous concept. A data set's
-row are essentially unlabeled, other than an implicit integer index that can be
+rows are essentially unlabeled, other than an implicit integer index that can be
accessed during the ``DATA`` step (``_N_``).
In pandas, if no index is specified, an integer index is also used by default
@@ -87,7 +87,7 @@ A SAS data set can be built from specified values by
placing the data after a ``datalines`` statement and
specifying the column names.
-.. code-block:: none
+.. code-block:: sas
data df;
input x y;
@@ -121,7 +121,7 @@ will be used in many of the following examples.
SAS provides ``PROC IMPORT`` to read csv data into a data set.
-.. code-block:: none
+.. code-block:: sas
proc import datafile='tips.csv' dbms=csv out=tips replace;
getnames=yes;
@@ -156,7 +156,7 @@ Exporting Data
The inverse of ``PROC IMPORT`` in SAS is ``PROC EXPORT``
-.. code-block:: none
+.. code-block:: sas
proc export data=tips outfile='tips2.csv' dbms=csv;
run;
@@ -178,7 +178,7 @@ Operations on Columns
In the ``DATA`` step, arbitrary math expressions can
be used on new or existing columns.
-.. code-block:: none
+.. code-block:: sas
data tips;
set tips;
@@ -207,7 +207,7 @@ Filtering
Filtering in SAS is done with an ``if`` or ``where`` statement, on one
or more columns.
-.. code-block:: none
+.. code-block:: sas
data tips;
set tips;
@@ -233,7 +233,7 @@ If/Then Logic
In SAS, if/then logic can be used to create new columns.
-.. code-block:: none
+.. code-block:: sas
data tips;
set tips;
@@ -262,7 +262,7 @@ Date Functionality
SAS provides a variety of functions to do operations on
date/datetime columns.
-.. code-block:: none
+.. code-block:: sas
data tips;
set tips;
@@ -307,7 +307,7 @@ Selection of Columns
SAS provides keywords in the ``DATA`` step to select,
drop, and rename columns.
-.. code-block:: none
+.. code-block:: sas
data tips;
set tips;
@@ -343,7 +343,7 @@ Sorting by Values
Sorting in SAS is accomplished via ``PROC SORT``
-.. code-block:: none
+.. code-block:: sas
proc sort data=tips;
by sex total_bill;
@@ -369,7 +369,7 @@ SAS determines the length of a character string with the
and `LENGTHC `__
functions. ``LENGTHN`` excludes trailing blanks and ``LENGTHC`` includes trailing blanks.
-.. code-block:: none
+.. code-block:: sas
data _null_;
set tips;
@@ -395,7 +395,7 @@ SAS determines the position of a character in a string with the
``FINDW`` takes the string defined by the first argument and searches for the first position of the substring
you supply as the second argument.
-.. code-block:: none
+.. code-block:: sas
data _null_;
set tips;
@@ -419,7 +419,7 @@ Substring
SAS extracts a substring from a string based on its position with the
`SUBSTR `__ function.
-.. code-block:: none
+.. code-block:: sas
data _null_;
set tips;
@@ -442,7 +442,7 @@ The SAS `SCAN `__
functions change the case of the argument.
-.. code-block:: none
+.. code-block:: sas
data firstlast;
input String $60.;
@@ -516,7 +516,7 @@ types of joins are accomplished using the ``in=`` dummy
variables to track whether a match was found in one or both
input frames.
-.. code-block:: none
+.. code-block:: sas
proc sort data=df1;
by key;
@@ -572,7 +572,7 @@ operations, and is ignored by default for aggregations.
One difference is that missing data cannot be compared to its sentinel value.
For example, in SAS you could do this to filter missing values.
-.. code-block:: none
+.. code-block:: sas
data outer_join_nulls;
set outer_join;
@@ -615,7 +615,7 @@ SAS's PROC SUMMARY can be used to group by one or
more key variables and compute aggregations on
numeric columns.
-.. code-block:: none
+.. code-block:: sas
proc summary data=tips nway;
class sex smoker;
@@ -640,7 +640,7 @@ In SAS, if the group aggregations need to be used with
the original frame, it must be merged back together. For
example, to subtract the mean for each observation by smoker group.
-.. code-block:: none
+.. code-block:: sas
proc summary data=tips missing nway;
class smoker;
@@ -679,7 +679,7 @@ replicate most other by group processing from SAS. For example,
this ``DATA`` step reads the data by sex/smoker group and filters to
the first entry for each.
-.. code-block:: none
+.. code-block:: sas
proc sort data=tips;
by sex smoker;
@@ -719,7 +719,7 @@ Data Interop
pandas provides a :func:`read_sas` method that can read SAS data saved in
the XPORT or SAS7BDAT binary format.
-.. code-block:: none
+.. code-block:: sas
libname xportout xport 'transport-file.xpt';
data xportout.tips;