BUG: groupby with std aggregation of pandas integer dtype throws exception: 'IntegerArray' object has no attribute 'reshape'
- [x ] I have checked that this issue has not already been reported.

- [x ] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
df = pd.DataFrame({'a': [1,1,1,2,2],'b': [1,2,3,4,5]})
df['b'] = df['b'].astype(pd.Int32Dtype())
df.groupby('a').agg('std') # Error 'IntegerArray' object has no attribute 'reshape'. The same error occurs with all pandas integer types

```

#### Problem description

For all integer pandas dtypes the code expects an IntegerArray to have the reshape function as is the case with numpy arrays.
It is possible that the error will also occur with other operations performed after a groupby, this has only been checked for 'std'.
The error occurs at
pandas\core\groupby\groupby.py", line 2491, in _get_cythonized_result
    vals = vals.reshape((-1, 1))

#### Expected Output

The same output as with a numpy data type, for example above this would be:

 
a 	 b
1 	1.000000
2 	0.707107



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

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.112+
Version          : #1 SMP Thu Jul 23 08:00:38 PDT 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.3
numpy            : 1.18.5
pytz             : 2018.9
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 50.3.0
Cython           : 0.29.21
pytest           : 3.6.4
hypothesis       : None
sphinx           : 1.8.5
blosc            : None
feather          : 0.4.1
xlsxwriter       : None
lxml.etree       : 4.2.6
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 5.5.0
pandas_datareader: 0.9.0
bs4              : 4.6.3
bottleneck       : 1.3.2
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 2.5.9
pandas_gbq       : 0.13.2
pyarrow          : 0.14.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.19
tables           : 3.4.4
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.1.0
xlwt             : 1.3.0
numba            : 0.48.0

</details>
