ENH: pandas.DataFrame.pivot option to output hierarchically indexed rows


#### Is your feature request related to a problem?
When I use `pivot` or `pivot_table` and pass a list of `values`, I get a multiindex on the columns, as the docs say. However, in my case I want the output to be hierarchically indexed by rows.

#### Describe the solution you'd like

It would be nice to have a `indexing_axis` kwarg in `pivot` and `pivot_table` so I could pass `indexing_axis='rows'` and get a multiindex on the rows instead of on the columns.

#### Describe alternatives you've considered

Can be fixed by running `df_pivoted.stack()`, but it would be nice to not have to do this as a separate step.


```python
df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
                         "bar", "bar", "bar", "bar"],
                   "B": ["one", "one", "one", "two", "two",
                         "one", "one", "two", "two"],
                   "C": ["small", "large", "large", "small",
                         "small", "large", "small", "small",
                         "large"],
                   "D": [1, 2, 2, 3, 3, 4, 5, 6, 7],
                   "E": [2, 4, 5, 5, 6, 6, 8, 9, 9]})

df_pivoted = df.pivot_table(index=['A','C'], columns='B', values=['D','E'])
# df_pivoted = df.pivot_table(index=['A','C'], columns='B', values=['D','E'], indexing_axis='rows') # this is what I want to be able to do

df_pivoted.stack() # this is what I want the result to look like

```

