Inconsistencies in index comparisons
Comparing indexes returns two different data types. This is problematic since one of the types is a bool while the other is a Series which [explicitly can't be treated in a bool context](http://pandas.pydata.org/pandas-docs/stable/gotchas.html#using-if-truth-statements-with-pandas). Not to mention that the next section says `==` returns a Series object.

```
import pandas as pd

print pd.__version__
#0.14.0

index = pd.Int64Index([1, 2, 3])

print index == pd.Int64Index([])
# False
print index == pd.Int64Index([1])
# [True, False, False]
print index == pd.Int64Index([1, 2])
# False
print index == pd.Int64Index([4, 5, 6])
# [False, False, False]

series = pd.Series([1, 2, 3])

print series == pd.Series([1, 2])
# ValueError: Series lengths must match to compare

```

I'd suggest that comparing indexes with different lengths raise a `ValueError` like `Series` do. Possibly keeping the 1 element vs many as a special case
