Add exponentiation function similar to add() or sub()
Currently if I exponentiate a DataFrame with a Series, the indexing joining logic is performed on the columns. This means the following:

``` python
>>> data = pandas.DataFrame({"a": [1, 2, 3, np.nan], "b": [23, 4, 5, np.nan]}, index=["ax", "bx", "cx", "dx"])
>>> series = pandas.Series([2,2,3, 1], index=["ax", "bx", "cx", "dx"])
>>> data ** series

     a  ax   b  bx  cx  dx
ax   1 NaN NaN NaN NaN NaN
bx NaN NaN NaN NaN NaN NaN
cx NaN NaN NaN NaN NaN NaN
dx NaN NaN NaN NaN NaN NaN

```

IOW, the joining happened on columns and not on rows. The only way I know to do this is to do `(data.T ** series).T`, which is kind of ugly. The addition of a pow() or exponentiate() function would allow me to use a specific axis to exponentiate and avoid this problem.
