"SpecificationError: nested dictionary is ambiguous in aggregation" in a certain case of groupby-aggregation
All of these examples for using `agg` work fine:
```
import pandas as pd
df = pd.DataFrame({"A":['A','A','B','B','B'],
                   "B":[1,2,1,1,2],
                   "C":[9,8,7,6,5]})
df.groupby('A')[['B','C']].agg({'B':'sum','C':'count'})
df.groupby('A')[['B','C']].agg({'B':['sum','count'],'C':'count'})
df.groupby('A')[['B']].agg('sum')
df.groupby('A')['B'].agg('sum')
```
This one throws a future warning as mentioned [here](https://github.com/pandas-dev/pandas/pull/15931):
```
df.groupby('A')['B'].agg({'B':['sum','count']})
```
This one works just fine:
```
df.groupby('A')[['B','C']].agg({'B':'sum'})
```
But this one throws an error (I'm aware this expression isn't necessary):
```
df.groupby('A')[['B']].agg({'B':'sum'})
```
> SpecificationError: nested dictionary is ambiguous in aggregation

Why does it throw this error?

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.8.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 79 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.24.1
pytest: 3.9.1
pip: 19.0.1
setuptools: 40.8.0
Cython: 0.29.5
numpy: 1.15.4
scipy: 1.2.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: 1.8.4
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.9
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.9
feather: None
matplotlib: 3.0.2
openpyxl: 2.6.0
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml.etree: 4.3.1
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.2.18
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.2.1
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
