DOC: docstring to series.unique
- [x] closes #20075 
- [x] tests added / passed
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

seems that no one has picked this up. moving _shared_doc['unique'] used by Series.unique() only to Series.unique.
```
################################################################################
####################### Docstring (pandas.Series.unique) #######################
################################################################################

Return unique values of Series object.

Uniques are returned in order of appearance. Hash table-based unique,
therefore does NOT sort.

Returns
-------
unique values.
  - If the input is an Index, the return is an Index
  - If the input is a Categorical dtype, the return is a Categorical
  - If the input is a Series/ndarray, the return will be an ndarray

See Also
--------
unique : return unique values of 1d array-like objects.
Index.unique : return Index with unique values from an Index object.

Examples
--------
>>> pd.Series([2, 1, 3, 3], name='A').unique()
array([2, 1, 3])

>>> pd.Series([2] + [1] * 5).unique()
array([2, 1])

>>> pd.Series([pd.Timestamp('20160101') for _ in range(3)]).unique()
array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')

>>> pd.Series([pd.Timestamp('20160101', tz='US/Eastern')                        for _ in range(3)]).unique()
array([Timestamp('2016-01-01 00:00:00-0500', tz='US/Eastern')],
      dtype=object)

An unordered Categorical will return categories in the order of
appearance.

>>> pd.Series(pd.Categorical(list('baabc'))).unique()
[b, a, c]
Categories (3, object): [b, a, c]

An ordered Categorical preserves the category ordering.

>>> pd.Series(pd.Categorical(list('baabc'), categories=list('abc'),                                      ordered=True)).unique()
[b, a, c]
Categories (3, object): [a < b < c]

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.Series.unique" correct. :)
```
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```diff
@@            Coverage Diff             @@
##           master   #20474      +/-   ##
==========================================
- Coverage   91.85%   91.82%   -0.03%     
==========================================
  Files         152      152              
  Lines       49231    49248      +17     
==========================================
+ Hits        45220    45224       +4     
- Misses       4011     4024      +13
```

| Flag | Coverage Δ | |
|---|---|---|
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| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20474?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/series.py](https://codecov.io/gh/pandas-dev/pandas/pull/20474/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvc2VyaWVzLnB5) | `93.84% <ø> (ø)` | :arrow_up: |
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| [pandas/core/indexes/period.py](https://codecov.io/gh/pandas-dev/pandas/pull/20474/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9wZXJpb2QucHk=) | `92.61% <0%> (ø)` | :arrow_up: |
| ... and [5 more](https://codecov.io/gh/pandas-dev/pandas/pull/20474/diff?src=pr&el=tree-more) | |

------

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> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20474?src=pr&el=footer). Last update [4fb963b...4931fcf](https://codecov.io/gh/pandas-dev/pandas/pull/20474?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
 @TomAugspurger comments welcome 👍  @jorisvandenbossche does it look good? @minggli Thanks a lot! Thanks @jorisvandenbossche 