is_list_like should return false for tuples
#### Code Sample, a copy-pastable example if possible

```python
In [2]: pd.core.dtypes.common.is_list_like((2,3))
Out[2]: True
```

#### Problem description

We discussed several times the fact that tuples in pandas should _not_ be considered collections of things, but rather
- ``MultiIndex`` keys, or
- combinations of keys, e.g. one for each dimension of a ``DataFrame``

(simple way to discriminate: if you could easily add an element, it is a collection; if instead the number of elements is somewhat hardcoded, it is not).

It is perfectly natural, and would solve problems/hacks such as

https://github.com/pandas-dev/pandas/commit/32ee9732b823448b87848f6bcaefdc762868999c#diff-1e79abbbdd150d4771b91ea60a4e1cc7R2701

https://github.com/pandas-dev/pandas/pull/24697#issuecomment-453078627

... and many others, to change the behavior of ``is_list_like``, which is used in many places.

See #23061 for a similar fix (although the similarity breaks whereas ``set``s are _intrinsically_ different from a ``list``, while for ``tuple``s it is a design decision).

I do expect some tests to break, and I also expect that in some cases, we'll want to preserve backwards compatibility... but at least let's set a sane default.

#### Expected Output

``False``

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: 040f06f731a09fc6e0663cada6697f6602b36f1d
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-8-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+1282.g040f06f73
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.28.4
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.2.2.post1634.dev0+ge8120cf6d
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml.etree: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1
gcsfs: None

</details>
