df.agg gives a TypeError when sending more than one argument with
#### Code Sample

```python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,30,size=(30, 4)), columns=list('ABCD'))
df = df.set_index(pd.date_range('2018-04-18 06:00:00', '2018-04-22 06:00:00', periods=30))
df['B'][5:15] = np.nan

df.agg('sum', axis=1)  # this works
df.agg('sum', skipna=False)  # this works
# but I want both
df.agg('sum', axis=1, skipna=False)  # this breaks
# TypeError: ("'str' object is not callable", 'occurred at index 2018-04-18 06:00:00')
```
#### Problem description

I need to pass both arguments to `sum`, but giving both gives an error. It works separately.
I need to specify the `aggfunc` as a "variable", since it won't always be the same.

This is a working alternative, but feels hacky when a built-in method is there to do the job:
```py
getattr(df, 'sum')(axis=1, skipna=False)
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.3
pytest: 3.6.3
pip: 18.0
setuptools: 40.0.0
Cython: 0.28.4
numpy: 1.14.5
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.5
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.4
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.5
lxml: 4.2.3
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.10
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
