ENH: added nunique function to Index
Added `nunique` function to `Index` same as `Series`. 

I like all the tests!

I would rather see this added in core/base.py (and  then remove the Series) one
you can leave some of the tests but add a couple in test_base

did you cover datetime/period index for tests?
 Sure. I'll try it.

Actually tests are derived from `test_series.py`. I'll prepare more tests for time-related indexes.
 I've moved `value_counts`, `unique` and `nunique` to the base class, and added more tests. Could you review this?
 FYI, I find it helpful to pull master and rebase when I push a PR 
(you don't have to , but always nice to get an auto merge), which are usually caused by release note conflicts
 also for some reason travis is not picking this up...can you rebase and force push?
 Rebased, and I'll take care.

Test has passed.
 can you move the imports to the top of the test script? 
better to just have them centralized.

was a little leary of a `.value_counts()` on an index returning a Series, but it DOES make sense.

can you add a timezone aware series & index in the test_base/Ops/objs.py (all should work, but not sure that case is there).
 This is great. I use such functionality all the time and indeed wrap like `pd.Series(s.index.tolist()).value_counts()`. 

+1 for `.value_counts()` added to base `Index` class.
 @nehalecky thanks for the feedback!

see #6382 for methods/properties that I think should be moved/changed to the OpsMin (some more tricky than others). Anything else pls comment.
 @jreback When I include tz series and index, I get `ValueError: Cannot compare tz-naive and tz-aware timestamps` during `min` and `max` tests. Maybe `Timestamp` compares checking `tzinfo` property which `datetime64` doesn't have?
 can you post the comparion? (e.g. you need to have the test use a Timestamp with a tz otherwise you SHOULD get that error).
 Sorry, I'm reffering to existing `TestIndexOps.test_ops` (L189).  Tests for `test_value_counts_unique_nunique` can be passed including tz. I pushed my current code.

Is it OK for me to do:
- Inculde tz-related `Series` and `Index` to `self.obj`.
- Modify 'TestIndexOps.test_ops' to exclude tz-related `Series` and `Index` from the arguments.
 These should all work (which is what the structure tests)

I think you need to use `keep_tz` when you create the series (so that the tz are kept!)

```
In [14]: i = tm.makeDateIndex(10).tz_localize(tz='US/Eastern')

In [15]: i
Out[15]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2000-01-03 00:00:00-05:00, ..., 2000-01-14 00:00:00-05:00]
Length: 10, Freq: B, Timezone: US/Eastern

In [16]: i.to_series(keep_tz=True).value_counts()
Out[16]: 
2000-01-05 00:00:00-05:00    1
2000-01-11 00:00:00-05:00    1
2000-01-14 00:00:00-05:00    1
2000-01-04 00:00:00-05:00    1
2000-01-07 00:00:00-05:00    1
2000-01-10 00:00:00-05:00    1
2000-01-13 00:00:00-05:00    1
2000-01-03 00:00:00-05:00    1
2000-01-06 00:00:00-05:00    1
2000-01-12 00:00:00-05:00    1
dtype: int64

In [17]: i.to_series(keep_tz=True).max()
Out[17]: Timestamp('2000-01-14 00:00:00-0500', tz='US/Eastern', offset='B')
```
 Thanks. I feel I could understand the problem now, the error isn't caused from `min` or `max` itselves, but by comparison done in `AssertEqual`

```
>>> i = tm.makeDateIndex(10).tz_localize(tz='US/Eastern')
# What TestIndexOps.test_ops does:
>>> i.max() == i.values.max()
ValueError: Cannot compare tz-naive and tz-aware timestamps
>>> i.values.max() == i.max()
False
>>> i.values.max().tolist() == i.max().value
True
```

Changing the test logic seems to be a workaround, but `Timestamp` class should be changed to allow the comparison with `datetime64`? If I still misunderstood, please let me know.
 you can't really compare `Timestamp` WITH a tz with a `np.datetime64` which does not have a tz (I know it shows that it does, but that's just a local representation), their is a proposal to 'fix' this (see http://mail.scipy.org/pipermail/numpy-discussion/2014-March/069282.html thread).

These SHOULD compare equal though (but because of the tz are not).

```
In [26]: np.datetime64('2001-01-01 00:00:00').astype('M8[ns]').astype('int64')
Out[26]: 978325200000000000

In [29]: x = Timestamp('20010101').tz_localize('EST')
In [34]: x.asm8
Out[34]: numpy.datetime64('2001-01-01T00:00:00.000000000-0500')

In [35]: x.value
Out[35]: 978325200000000000

```

for now. just text those cases explicity
 Thanks! I've added error handling, and rebased onto latest master.
 Understood. I've modified tests to use `series_equal` for `value_counts` and `numpy_array_equal` for `unique`.

And is the current `value_counts` behavior ok to include `NaT`?
 You mean like this? yes NaT should be included

```
In [64]: x = pd.DatetimeIndex(date_range('20130101',periods=10).take(np.random.randint(0,10,size=100)).tolist() + [pd.NaT,pd.NaT])

In [65]: x
Out[65]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2013-01-10, ..., NaT]
Length: 102, Freq: None, Timezone: None

In [66]: x.to_series().value_counts()
Out[66]: 
2013-01-06    16
2013-01-05    13
2013-01-08    11
2013-01-07    11
2013-01-10    11
2013-01-01     9
2013-01-03     9
2013-01-09     7
2013-01-02     7
2013-01-04     6
NaT            2
dtype: int64
```
 thanks @sinhrks 

lots of nice PR's from you!

keep em coming

FYI my comments about the NaT testing were really just for your information...this PR is good!
 Thank you for your review & info. I remember. 

I owe much to pandas and hope to assist a little!
 no thank you for the contributions!

keep em coming
