BUG: DataFrame.groupby() interprets tuple as list of keys 
State: closed

- [x] closes #17979 
- [x] tests added / passed
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

```
In [2]: df = pd.DataFrame([[1, 2, 3, 4], [3, 4, 5, 6], [1, 4, 2, 3]],
   ...:                            columns=pd.MultiIndex.from_arrays([['a', 'b', 'b', 'c'],
   ...:                                                               [1, 1, 2, 2]]))

In [3]: df.groupby([('b', 1)]).groups
Out[3]: {2: Int64Index([0], dtype='int64'), 4: Int64Index([1, 2], dtype='int64')}

In [4]: df.groupby(('b', 1)).groups
Out[4]: {2: Int64Index([0], dtype='int64'), 4: Int64Index([1, 2], dtype='int64')}
```

Labels:
name: Bug
name: Groupby
name: MultiIndex

Comments:
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=h1) Report
> Merging [#17996](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/881ee30b443f8b9651068b819ecd43adca5789b5?src=pr&el=desc) will **decrease** coverage by `0.01%`.
> The diff coverage is `100%`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/17996/graphs/tree.svg?token=eZ4WkYLtcO&src=pr&height=150&width=650)](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #17996      +/-   ##
==========================================
- Coverage   91.25%   91.23%   -0.02%     
==========================================
  Files         163      163              
  Lines       50115    50116       +1     
==========================================
- Hits        45730    45722       -8     
- Misses       4385     4394       +9
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `89.04% <100%> (ø)` | :arrow_up: |
| #single | `40.32% <0%> (+0.02%)` | :arrow_up: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/groupby.py](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZ3JvdXBieS5weQ==) | `92.04% <100%> (ø)` | :arrow_up: |
| [pandas/io/gbq.py](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=tree#diff-cGFuZGFzL2lvL2dicS5weQ==) | `25% <0%> (-58.34%)` | :arrow_down: |
| [pandas/core/frame.py](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZnJhbWUucHk=) | `97.75% <0%> (-0.1%)` | :arrow_down: |

------

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> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=footer). Last update [881ee30...afb0031](https://codecov.io/gh/pandas-dev/pandas/pull/17996?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

add a whatsnew for 0.21.1.

if you want to try to clean up all of that if logic would be a big +
`match_axis_length` boils down to whether the keys need to be converted by [`_asarray_tuplesafe`](https://github.com/GuessWhoSamFoo/pandas/blob/ec4a3e76905d658db2a2e48aba99c1a799eda172/pandas/core/groupby.py#L2792). Since `any_arraylike` will be true for this case, the intuition is that there is no need to worry about `match_axis_length`
lgtm, ping on green.
@jreback Rebased and green 👍



thanks @GuessWhoSamFoo keep em coming!