update 0.9.1 whatsnew to add where/mask commentary

doc/source/v0.9.1.txt

@@ -42,14 +42,44 @@ New features
   - DataFrame has new `where` and `mask` methods to select values according to a
     given boolean mask (GH2109_, GH2151_)
 
-    .. ipython:: python
+	DataFrame currently supports slicing via a boolean vector the same length as the DataFrame (inside the `[]`).
+	The returned DataFrame has the same number of columns as the original, but is sliced on its index.
+
+        .. ipython:: python
+
+    	    df = DataFrame(np.random.randn(5, 3), columns = ['A','B','C'])
+
+	    df
+
+	    df[df['A'] > 0]
+
+	If a DataFrame is sliced with a DataFrame based boolean condition (with the same size as the original DataFrame),
+	then a DataFrame the same size (index and columns) as the original is returned, with
+	elements that do not meet the boolean condition as `NaN`. This is accomplished via
+	the new method `DataFrame.where`. In addition, `where` takes an optional `other` argument for replacement.
+
+	.. ipython:: python
+
+	   df[df>0]
+
+	   df.where(df>0)
+
+	   df.where(df>0,-df)
+
+	Furthermore, `where` now aligns the input boolean condition (ndarray or DataFrame), such that partial selection
+	with setting is possible. This is analagous to partial setting via `.ix` (but on the contents rather than the axis labels)
+
+	.. ipython:: python
 
-        df = DataFrame(np.random.randn(5, 3))
+	   df2 = df.copy()
+   	   df2[ df2[1:4] > 0 ] = 3
+	   df2
 
-        df.where(df > 0, -df)
+	`DataFrame.mask` is the inverse boolean operation of `where`.
 
-        df.mask(df < 0)
+	.. ipython:: python
 
+	   df.mask(df<=0)
 
   - Enable referencing of Excel columns by their column names (GH1936_)