update docs

Author: jreback

doc/source/user_guide/reshaping.rst

@@ -824,11 +824,11 @@ We can 'explode' this transforming each element of a list-like to a row, by usin
 
    df['values'].explode()
 
-You can easily join this with the original to get an expanded ``DataFrame``.
+You can also explode the column in the ``DataFrame``.
 
 .. ipython:: python
 
-   df[['keys']].join(df['values'].explode())
+   df.explode('values')
 
 :meth:`Series.explode` will replace empty lists with ``np.nan`` and preserve scalar entries. The dtype of the resulting ``Series`` is always ``object``.
 
@@ -850,6 +850,4 @@ Creating a long form DataFrame is now straightforward using explode and chained
 
 .. ipython:: python
 
-   exploded = df.var1.str.split(',').explode()
-   exploded
-   df[['var2']].join(exploded)
+   df.assign(var1=df.var1.str.split(',')).explode('var1')

doc/source/whatsnew/v0.25.0.rst

@@ -187,15 +187,9 @@ The repr now looks like this:
 Series.explode to split list-like values to rows
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-:class:`Series` has gained the :meth:`Series.explode` method to transform list-likes to individual rows. See :ref:`section on Exploding list-like column <reshaping.explode>` in docs for more information (:issue:`16538`, :issue:`10511`)
+:class:`Series` and :class:`DataFrame` have gained the :meth:`DataFrame.explode` methods to transform list-likes to individual rows. See :ref:`section on Exploding list-like column <reshaping.explode>` in docs for more information (:issue:`16538`, :issue:`10511`)
 
 
-.. ipython:: python
-
-    s = pd.Series([[1, 2, 3], np.nan, [], [3, 4]])
-    s
-    s.explode()
-
 Here is a typical usecase. You have comma separated string in a column.
 
 .. ipython:: python
@@ -208,9 +202,7 @@ Creating a long form ``DataFrame`` is now straightforward using chained operatio
 
 .. ipython:: python
 
-    exploded = df.var1.str.split(',').explode()
-    exploded
-    df[['var2']].join(exploded)
+    df.assign(var1=df.var1.str.split(',')).explode('var1')
 
 .. _whatsnew_0250.enhancements.other: