BUG: Default to stat axis for SparseDataFrame when axis=None
Title is self-explanatory.  Closes #13048.

Surprisingly, there aren't a lot of places where `axis` is used when calling a cumulative function except for `SparseDataFrame` because that is the only (non-deprecated) multi-dimensional sparse object.
 @jreback : would be great to get some feedback regarding the `argmin`/`argmax` failure (due to the `SparseDataFrame` not accepting scalar input for `__array_wrap__`) as well the potential aliasing of `idxmin` to `argmin` (and `idxmax` to `argmax`) for `SparseDataFrame`
 @gfyoung can you a copy-pastable example here of issue with `argmax/min` we generally don't support them AFAICT on non `Series`.
 ``` python
>>> from pandas import SparseDataFrame
>>> import numpy as np
>>> sdf = SparseDataFrame([[1, 2, 3], [4, 5, 6]])
>>> np.argmin(sdf)
...
ValueError: Must pass 2-d input
```

I am not advocating that it be added to the list of supported methods, but I see no reason to test it per se in the list of functions for `test_numpy_func_call` (for `SparseDataFrame` that is)...that's all.  Or rather, we should test it that raises like this?  Not sure...
 doesn't work on dense either. I suppose you could make a separate issue about this. Its not high on priority list though.

```
In [5]: np.argmin(sdf.to_dense())
ValueError: Must pass 2-d input
```
 @jreback : I don't consider to be an issue, as the documentation makes it clear that you should call the `DataFrame.idxmin` or `DataFrame.idxmax` instead of the `np.argmin` or `np.argmax`.  I just wanted to double check that I could take it out of the list.
 @gfyoung yep, take em out. ping when green.
 @jreback : Travis is all green.  Ready to merge if there is nothing else.
 thanks!
