implement shift_quarters --> apply_index for quarters and years
`tslibs.offsets.shift_quarters` should look like the the lovechild of `offsets.shift_months` and `QuarterOffset.apply`.  It may be possible to de-duplicate some of that* at some point.

We get `apply_index` methods for all four `YearOffset` subclasses and all four `QuarterOffset` subclasses.  (Previously there were implementations for the non-business versions, but they went through a code path that I found fragile).  `BeginMixin` is no longer used, removed.

All 12 of the (non-custom) Month+Quarter+Year offset subclasses are now parametrized stubs with the actual implementations unified in parent classes.

Small cleanups and notes in offsets.

\* It would be convenient to be able to specify a function to accept either a `datetime` or a `pandas_datetimestruct` in cases where they quack alike.  I tried to do a `ctypedef fused datetimelike` but cython objected.  Any thoughts?

```
asv continuous -f 1.1 -E virtualenv master HEAD -b offset
[...]
       before           after         ratio
     [262e8ff3]       [21504bfd]
-      18.4±0.9μs      16.7±0.06μs     0.91  offset.CBDay.time_custom_bday_apply_dt64
-        519±20ms        458±0.3ms     0.88  offset.SemiMonthOffset.time_end_apply_index
-        77.7±6ms      67.7±0.09ms     0.87  timeseries.ToDatetime.time_cache_false_with_dup_string_tzoffset_dates
-        542±20ms          459±2ms     0.85  offset.SemiMonthOffset.time_begin_incr_rng
-         209±3μs        132±0.2μs     0.63  offset.CBMonthBegin.time_custom_bmonthbegin_incr_n
-      21.5±0.1ms         6.82±1ms     0.32  offset.ApplyIndex.time_apply_series(<YearBegin: month=1>)
-      23.4±0.6ms      6.82±0.09ms     0.29  offset.ApplyIndex.time_apply_series(<QuarterBegin: startingMonth=3>)
-      22.0±0.5ms      5.17±0.09ms     0.23  offset.ApplyIndex.time_apply_index(<QuarterBegin: startingMonth=3>)
-      19.8±0.4ms       4.64±0.1ms     0.23  offset.ApplyIndex.time_apply_index(<YearBegin: month=1>)
-         487±1ms      8.13±0.06ms     0.02  offset.ApplyIndex.time_apply_series(<YearEnd: month=12>)
-        502±20ms      7.14±0.07ms     0.01  offset.ApplyIndex.time_apply_series(<QuarterEnd: startingMonth=3>)
-       494±0.4ms       6.02±0.2ms     0.01  offset.ApplyIndex.time_apply_index(<YearEnd: month=12>)
-        555±20ms       5.64±0.2ms     0.01  offset.ApplyIndex.time_apply_index(<QuarterEnd: startingMonth=3>)
-           1.52s         11.3±1ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessYearEnd: month=12>)
-           1.41s       8.17±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessYearBegin: month=1>)
-           1.82s       10.0±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessQuarterEnd: startingMonth=3>)
-           1.47s       8.07±0.6ms     0.01  offset.ApplyIndex.time_apply_index(<BusinessQuarterEnd: startingMonth=3>)
-           1.57s       8.49±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessQuarterBegin: startingMonth=3>)
-           1.66s      8.35±0.09ms     0.01  offset.ApplyIndex.time_apply_index(<BusinessYearEnd: month=12>)
-           1.53s       6.51±0.1ms     0.00  offset.ApplyIndex.time_apply_index(<BusinessQuarterBegin: startingMonth=3>)
-           1.63s      6.21±0.06ms     0.00  offset.ApplyIndex.time_apply_index(<BusinessYearBegin: month=1>)
```

Running a larger version now.

- [ ] closes #xxxx
- [x] tests added / passed --> apply_index for all relevant classes, make sure to hit negative n
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

Travis error looks unrelated:
```
_______ TestDataFramePlots.test_parallel_coordinates_with_sorted_labels ________
[gw0] linux -- Python 3.6.3 /home/travis/miniconda3/envs/pandas/bin/python
self = <pandas.tests.plotting.test_misc.TestDataFramePlots object at 0x7ff86427ea20>
    def test_parallel_coordinates_with_sorted_labels(self):
        """ For #15908 """
        from pandas.plotting import parallel_coordinates
        df = DataFrame({"feat": [i for i in range(30)],
                        "class": [2 for _ in range(10)] +
                        [3 for _ in range(10)] +
                        [1 for _ in range(10)]})
        ax = parallel_coordinates(df, 'class', sort_labels=True)
        polylines, labels = ax.get_legend_handles_labels()
        color_label_tuples = \
            zip([polyline.get_color() for polyline in polylines], labels)
        ordered_color_label_tuples = sorted(color_label_tuples,
                                            key=lambda x: x[1])
        prev_next_tupels = zip([i for i in ordered_color_label_tuples[0:-1]],
                               [i for i in ordered_color_label_tuples[1:]])
        for prev, nxt in prev_next_tupels:
            # lables and colors are ordered strictly increasing
>           assert prev[1] < nxt[1] and prev[0] < nxt[0]
E           TypeError: '<' not supported between instances of 'list' and 'str'
pandas/tests/plotting/test_misc.py:221: TypeError
``` > Travis error looks unrelated:

*Maybe*, though as you know, we need all green to merge.  I'll double-check that the error wasn't spurious. # [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=h1) Report
> Merging [#18522](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/262e8ff367c9291c79c4df0c2daf4713de52abc0?src=pr&el=desc) will **increase** coverage by `<.01%`.
> The diff coverage is `100%`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/18522/graphs/tree.svg?src=pr&token=eZ4WkYLtcO&width=650&height=150)](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #18522      +/-   ##
==========================================
+ Coverage   91.32%   91.33%   +<.01%     
==========================================
  Files         163      163              
  Lines       49798    49780      -18     
==========================================
- Hits        45479    45465      -14     
+ Misses       4319     4315       -4
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `89.13% <100%> (+0.02%)` | :arrow_up: |
| #single | `40.8% <33.33%> (-0.06%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/tseries/offsets.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL3RzZXJpZXMvb2Zmc2V0cy5weQ==) | `96.9% <100%> (-0.05%)` | :arrow_down: |
| [pandas/io/gbq.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2lvL2dicS5weQ==) | `25% <0%> (-58.34%)` | :arrow_down: |
| [pandas/core/frame.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZnJhbWUucHk=) | `97.81% <0%> (-0.1%)` | :arrow_down: |
| [pandas/core/indexes/datetimes.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9kYXRldGltZXMucHk=) | `95.71% <0%> (+0.09%)` | :arrow_up: |
| [pandas/plotting/\_converter.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL3Bsb3R0aW5nL19jb252ZXJ0ZXIucHk=) | `65.25% <0%> (+1.81%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=footer). Last update [262e8ff...a8c6a9c](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
 # [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=h1) Report
> Merging [#18522](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/262e8ff367c9291c79c4df0c2daf4713de52abc0?src=pr&el=desc) will **increase** coverage by `<.01%`.
> The diff coverage is `100%`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/18522/graphs/tree.svg?src=pr&width=650&token=eZ4WkYLtcO&height=150)](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #18522      +/-   ##
==========================================
+ Coverage   91.32%   91.33%   +<.01%     
==========================================
  Files         163      163              
  Lines       49798    49780      -18     
==========================================
- Hits        45479    45465      -14     
+ Misses       4319     4315       -4
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `89.13% <100%> (+0.02%)` | :arrow_up: |
| #single | `40.8% <33.33%> (-0.06%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/tseries/offsets.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL3RzZXJpZXMvb2Zmc2V0cy5weQ==) | `96.9% <100%> (-0.05%)` | :arrow_down: |
| [pandas/io/gbq.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2lvL2dicS5weQ==) | `25% <0%> (-58.34%)` | :arrow_down: |
| [pandas/core/frame.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZnJhbWUucHk=) | `97.81% <0%> (-0.1%)` | :arrow_down: |
| [pandas/core/indexes/datetimes.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9kYXRldGltZXMucHk=) | `95.71% <0%> (+0.09%)` | :arrow_up: |
| [pandas/plotting/\_converter.py](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=tree#diff-cGFuZGFzL3Bsb3R0aW5nL19jb252ZXJ0ZXIucHk=) | `65.25% <0%> (+1.81%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=footer). Last update [262e8ff...a8c6a9c](https://codecov.io/gh/pandas-dev/pandas/pull/18522?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
 Not sure how it got to green given that I didn’t re-push... > Not sure how it got to green given that I didn’t re-push...

@jbrockmendel : I said "I'll double-check that the error wasn't spurious" i.e. I reran the build :smile:  lgtm. ready to go? >  i.e. I reran the build

Neat, thanks. More thorough asv run:

```
taskset 2 asv continuous -f 1.1 -E virtualenv master HEAD -b offset -b timedelta -b period -b timeseries
[...]
       before           after         ratio
     [262e8ff3]       [21504bfd]
+     19.4±0.04μs       22.5±0.7μs     1.16  offset.SemiMonthOffset.time_end_incr_n
-           40.7s            32.7s     0.80  gil.nogil_datetime_fields.time_period_to_datetime
-        23.8±1ms       7.11±0.2ms     0.30  offset.ApplyIndex.time_apply_series(<QuarterBegin: startingMonth=3>)
-      22.5±0.7ms      6.39±0.07ms     0.28  offset.ApplyIndex.time_apply_series(<YearBegin: month=1>)
-      21.8±0.4ms       5.28±0.2ms     0.24  offset.ApplyIndex.time_apply_index(<QuarterBegin: startingMonth=3>)
-      21.1±0.5ms       4.67±0.1ms     0.22  offset.ApplyIndex.time_apply_index(<YearBegin: month=1>)
-         507±9ms       7.46±0.4ms     0.01  offset.ApplyIndex.time_apply_series(<QuarterEnd: startingMonth=3>)
-        549±40ms       7.82±0.1ms     0.01  offset.ApplyIndex.time_apply_series(<YearEnd: month=12>)
-         508±6ms      5.95±0.06ms     0.01  offset.ApplyIndex.time_apply_index(<YearEnd: month=12>)
-        513±10ms       5.49±0.1ms     0.01  offset.ApplyIndex.time_apply_index(<QuarterEnd: startingMonth=3>)
-           1.43s       10.0±0.3ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessQuarterEnd: startingMonth=3>)
-           1.56s       10.3±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessYearEnd: month=12>)
-           1.48s       8.57±0.2ms     0.01  offset.ApplyIndex.time_apply_index(<BusinessYearEnd: month=12>)
-           1.50s       8.51±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessQuarterBegin: startingMonth=3>)
-           1.49s       7.91±0.3ms     0.01  offset.ApplyIndex.time_apply_index(<BusinessQuarterEnd: startingMonth=3>)
-           1.51s       7.87±0.2ms     0.01  offset.ApplyIndex.time_apply_series(<BusinessYearBegin: month=1>)
-           1.53s      6.76±0.08ms     0.00  offset.ApplyIndex.time_apply_index(<BusinessQuarterBegin: startingMonth=3>)
-           1.49s       6.13±0.2ms     0.00  offset.ApplyIndex.time_apply_index(<BusinessYearBegin: month=1>)
``` thanks!