BUG: fix Panel.fillna() ignoring axis parameter

This fixes #8251. It may need some more comprehensive tests but before I go too much farther I want to make sure the axis numbering scheme makes sense . The default behavior of `fillna` is to fill along `axis=0`. In the case of a DataFrame this fills along the columns. However, in the case of a Panel, filling along `axis=0` means you're filling along items. I'm not sure if that's the behavior that most users would think is the default. You might note that I also removed the references to what the behavior of each axis value is in the docstring since it gets a bit arbitrary when you consider both DataFrames and Panels.
Well, without restoring the categoricals, this test fails:

    ======================================================================
    ERROR: test_na_actions (pandas.tests.test_categorical.TestCategoricalAsBlock)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/home/stahlous/pd_dev/pandas/pandas/tests/test_categorical.py", line 2183, in test_na_actions
        tm.assert_frame_equal(res, df_exp_fill)
      File "/home/stahlous/pd_dev/pandas/pandas/util/testing.py", line 707, in assert_frame_equal
        check_exact=check_exact)
      File "/home/stahlous/pd_dev/pandas/pandas/util/testing.py", line 645, in assert_series_equal
        assert_attr_equal('dtype', left, right)
      File "/home/stahlous/pd_dev/pandas/pandas/util/testing.py", line 627, in assert_attr_equal
        assert_equal(left_attr,right_attr,"attr is not equal [{0}]" .format(attr))
      File "/home/stahlous/pd_dev/pandas/pandas/util/testing.py", line 610, in assert_equal
        assert a == b, "%s: %r != %r" % (msg.format(a,b), a, b)
    TypeError: data type not understood

    ----------------------------------------------------------------------

If  `_data.interpolate` does call `Categorical.fillna`, I didn't realize that. In the current implementation of `DataFrame.apply` I don't think it would make any difference since `convert_objects` clobbers categoricals. Even if that weren't the case, if the fill axis is orthogonal to the categorical axis you'll still lose the categoricals.

I'll ponder on this a little more this evening.