BUG/API: Index.append with mixed object/Categorical indices
Closes #14298, related to #13660 and #13767

This closes the `info()` issue with CategoricalIndex, but the underlying issue is actually related to Index.append, when appending mixed dtype index objects: 

```
In [11]: pd.Index(['a']).append(pd.CategoricalIndex(['a', 'b']))
...
AttributeError: 'Index' object has no attribute '_is_dtype_compat'
```

This error occurs when the calling index is not a Categorical (because of https://github.com/pandas-dev/pandas/blob/v0.19.0/pandas/indexes/base.py#L1439 the Categorical `_is_dtype_compat` method is used anyway).

But the question is, what should the result be of the above expression?

- a `CategoricalIndex` ? -> IMO not, as the calling index is not a CategoricalIndex, the result should also not be one (regardless of what is appended) -> so the intention of the code is IMO also not correct
- an object Index ? -> yes, this is also what 0.18.1 does

But, the more important discussion is *what to do when the calling index is a CategoricalIndex* ? In 0.18 (and in 0.19.0) this either returned a CategoricalIndex or raised an error:

```
In [13]: pd.__version__
Out[13]: u'0.18.1'

In [104]: pd.CategoricalIndex(['a', 'b']).append(pd.Index(['a']))
Out[104]: CategoricalIndex([u'a', u'b', u'a'], categories=[u'a', u'b'], ordered=False, dtype='category')

In [105]: pd.CategoricalIndex(['a', 'b']).append(pd.Index(['c']))
...
TypeError: cannot append a non-category item to a CategoricalIndex
```

But, for the `concat` case we decided to return an object dtyped Index in those cases instead of coercing or raising (see discussion in #13767 and the summary table with rules in https://github.com/pandas-dev/pandas/pull/13767#issuecomment-237806603). So the question is, do think that `append` should follow the same rules as `concat`. Or, do we want to be more flexible for `append`, and let it depend on the type of the calling Index?


cc @sinhrks 

In the current PR, I just removed the check for category, which is the more intrusive change, as now the return result will always be object dtype if not self and all objects to append are CategoricalIndex. 
I could also change the `if 'category' in typs:` check to `if self.is_categorical():`, which then keeps the current behaviour if the calling object is a CategoricalIndex.
 ## [Current coverage](https://codecov.io/gh/pandas-dev/pandas/pull/14545?src=pr) is 85.27% (diff: 100%)

> Merging [#14545](https://codecov.io/gh/pandas-dev/pandas/pull/14545?src=pr) into [master](https://codecov.io/gh/pandas-dev/pandas/branch/master?src=pr) will not change coverage

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```

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 OK, so I changed the PR to only fix the issue when the calling Index is not of Categorical dtype (which caused the bug), and left the behaviour of `CategoricalIndex.append(..)` alone. 
As a result `pd.Index(['a']).append(pd.CategoricalIndex(['a', 'b']))` works again (returning object Index as in 0.18.1).

That is probably the easiest for now, to have this fix in 0.19.1, but we should then discuss the behaviour of `Index.append(..)` a bit more in detail for 0.20 (whether to follow the same rules as `concat` or not).
 +1 on the behavior here (coercing Categorical to Index).

I'd feel slightly better if the monkey patching of `sys.stdout` was in a context manager

``` python
from contextlib import contextmanager

@contextmanager
def stdout():
    sys.stdout = StringIO()
    yield
    sys.stdout = sys.__stdout__
```

but not a huge deal.
 > I'd feel slightly better if the monkey patching of sys.stdout was in a context manager

I just copied the approach from other tests :-), so would be a nice clean-up in general!
 don't re-invent the wheel, the pattern is:

```
buf = StringIO()
df.info(buf=buf, null_counts=null_counts)
self.assertTrue(('non-null' in buf.getvalue()) is result)
```
