Implement CategoricalIndex

[jankatins]

When #7217 becomes available, it would be nice to also have a 'CategoricalIndex' so that the sorting behaviour based on levels will be preserved when a categorical becomes a index:

cats = pd.Categorical([1,2,3,4], levels=[4,2,3,1])
strings = ["a","b","c","d"]
values = [4,2,3,1]
df = pd.DataFrame({"strings":strings, "values":values}, index=cats)
df.index
# This should sort by levels but does not as there is no CategoricalIndex!
df.sort_index()

CC: @shoyer

[shoyer]

It occurs to me now (probably already obvious to others) that the implementation of Categorical is basically the same as a single level MultiIndex. So that would probably be a good starting point.

[jankatins]

I haven't looked into MultiIndex but in my mind it makes more sense to model it after a Int/string index or normal numpy backed ones, as Categorical is in my mind a np.array and so should simple get all the methods to make it work as a "backend" of an Index. The only difference to a string is that i can be differently sorted ("one" < "two" < "three") and that the categorical should be accessible like in Series.cat.

So this might be as easy as coping the Index type for string, make that accept only a Categoricalas input, make sure that the Index constructor maps to that and then see what breaks with a AttributeError.