groupby w/ only NULL-groups crashes since 0.23
#### Code Sample, a copy-pastable example if possible

```python
import numpy as np
import pandas as pd
import pandas.testing as pdt


# works:
df1 = pd.DataFrame({
    'g': [None, 'a'],
    'x': 1,
})
actual1 = df1.groupby('g')['x'].transform('sum')
expected1 = pd.Series([np.nan, 1.], name='x')

pdt.assert_series_equal(
    actual1,
    expected1,
)


# crashes:
df2 = pd.DataFrame({
    'g': [None],
    'x': 1,
})
actual2 = df2.groupby('g')['x'].transform('sum')
expected2 = pd.Series([np.nan], name='x')  # crashes with "ValueError: Length of passed values is 1, index implies 0"

pdt.assert_series_equal(
    actual2,
    expected2,
)
```
#### Problem description
`groupby` ignores groups that contain NULL-elements in any of the group columns. In that case, results of `transform` are NULL (NaN for floats, NaT for time, None for objects). The question is what happens if there are only "NULL groups":

- before pandas 0.23: an object column with `None` objects is created
- pandas 0.23: crash (`ValueError: Length of passed values is 1, index implies 0`)

#### Expected Output
A NULL-column according to the input data type.

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

<details>

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.49-moby
machine: x86_64
processor:
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.23.1
pytest: 3.4.0
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.0.0
pyarrow: 0.9.0
xarray: None
IPython: 5.7.0
sphinx: 1.6.7
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.0
xlrd: None
xlwt: None
xlsxwriter: 0.8.4
lxml: 3.8.0
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.8.1
s3fs: 0.1
fastparquet: None
pandas_gbq: None
pandas_datareader: None
```
</details>
