diff --git a/doc/source/getting_started/comparison/comparison_with_sql.rst b/doc/source/getting_started/comparison/comparison_with_sql.rst
index 366fdd546f58b..6a03c06de3699 100644
--- a/doc/source/getting_started/comparison/comparison_with_sql.rst
+++ b/doc/source/getting_started/comparison/comparison_with_sql.rst
@@ -49,6 +49,20 @@ With pandas, column selection is done by passing a list of column names to your
 Calling the DataFrame without the list of column names would display all columns (akin to SQL's
 ``*``).
 
+In SQL, you can add a calculated column:
+
+.. code-block:: sql
+
+    SELECT *, tip/total_bill as tip_rate
+    FROM tips
+    LIMIT 5;
+
+With pandas, you can use the :meth:`DataFrame.assign` method of a DataFrame to append a new column:
+
+.. ipython:: python
+
+    tips.assign(tip_rate=tips['tip'] / tips['total_bill']).head(5)
+
 WHERE
 -----
 Filtering in SQL is done via a WHERE clause.