ExtensionBlock.is_numeric is always False
#### Code Sample/Problem Description

Currently `ExtensionBlock.is_numeric` always returns `False`.  This can be problematic for extension arrays that are numeric, as this is used under the hood in places to filter to numeric columns in a `DataFrame`.  I'll be using `IntegerArray` as an example, but this in principle applies to any numeric extension array, e.g. `DecimalArray` in the testing suite, an extension array for units/uncertainties, etc.

Setup:
```python
In [2]: df = pd.DataFrame({'group': list('aaabbb'),
   ...:                    'val1': IntegerArray([0, 1, 2, np.nan, 3, 4]),
   ...:                    'val2': np.arange(6)})
   ...:                    

In [3]: df
Out[3]: 
  group val1  val2
0     a    0     0
1     a    1     1
2     a    2     2
3     b  NaN     3
4     b    3     4
5     b    4     5
```

The `IntegerArray` column is ignored by `DataFrame._get_numeric_data()`:
```python
In [4]: df._get_numeric_data()
Out[4]: 
   val2
0     0
1     1
2     2
3     3
4     4
5     5
```

This leads some numeric routines, such as `DataFrame.corr` ignoring the `IntegerArray` column:
```python
In [5]: df.corr()
Out[5]: 
      val2
val2   1.0
```

Likewise, `groupby` uses `ExtensionBlock.is_numeric` to filter to numeric columns for some operations, leading to the `IntegerArray` column being ignored, even if explicitly requested:
```python
In [6]: df.groupby('group').sum()
Out[6]: 
       val2
group      
a         3
b        12

In [7]: df.groupby('group')['val1', 'val2'].sum()
Out[7]: 
       val2
group      
a         3
b        12
```
#### Expected Output
I'd expect `ExtensionBlock.is_numeric` to return `True` when appropriate, and for behavior to be consistent with non-extension numeric dtypes.

My first impression is that this should be an attribute of the `ExtensionArray` or `ExtensionDtype` class that defaults to `False`, with numeric implementations setting the attribute to `True`, and `ExtensionBlock.is_numeric` would read the value from there.

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

<details>

INSTALLED VERSIONS
------------------
commit: 0370740034978d3a63d4b8e5e2c96ff54e7e08ba
python: 3.6.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.14.29-galliumos
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0.dev0+456.g0370740
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
