diff --git a/doc/source/computation.rst b/doc/source/computation.rst
index 4285767654e25..ff06c369e1897 100644
--- a/doc/source/computation.rst
+++ b/doc/source/computation.rst
@@ -323,7 +323,7 @@ compute the mean absolute deviation on a rolling basis:
 
    mad = lambda x: np.fabs(x - x.mean()).mean()
    @savefig rolling_apply_ex.png
-   s.rolling(window=60).apply(mad).plot(style='k')
+   s.rolling(window=60).apply(mad, raw=True).plot(style='k')
 
 .. _stats.rolling_window:
 
diff --git a/doc/source/cookbook.rst b/doc/source/cookbook.rst
index 4e61228d5c0ad..893642410af02 100644
--- a/doc/source/cookbook.rst
+++ b/doc/source/cookbook.rst
@@ -496,7 +496,7 @@ Unlike agg, apply's callable is passed a sub-DataFrame which gives you access to
    def Red(x):
       return functools.reduce(CumRet,x,1.0)
 
-   S.expanding().apply(Red)
+   S.expanding().apply(Red, raw=True)
 
 
 `Replacing some values with mean of the rest of a group