ValueError on df.agg if a list of functions is given
#### Code Sample

```python
import numpy as np
import pandas as pd

_arr = np.array([1,2,3,4,5,np.nan])
_arr2 = np.array([1,2,3,4,5,7])

df = pd.DataFrame({"A": _arr, "B": _arr2})

def perc_fun(q):
    def f(arr):
        return np.nanpercentile(arr, q)
    f.__name__ = f"p-{q}"
    return f
```

all is as expected here:

```python
perc_fun(10)(_arr)
>>> 1.4

df.agg(perc_fun(10))
>>> A    1.4
>>> B    1.5
>>> dtype: float64
```

but this dies:

```python
df.agg(["mean", perc_fun(10)])
```
<details>

TypeError                                 Traceback (most recent call last)
~/.local/lib/python3.7/site-packages/pandas/core/base.py in _aggregate_multiple_funcs(self, arg, _axis)
    553         try:
--> 554             return concat(results, keys=keys, axis=1, sort=False)
    555         except TypeError:

~/.local/lib/python3.7/site-packages/pandas/core/reshape/concat.py in concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
    280         copy=copy,
--> 281         sort=sort,
    282     )

~/.local/lib/python3.7/site-packages/pandas/core/reshape/concat.py in __init__(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)
    356                 )
--> 357                 raise TypeError(msg)
    358 

TypeError: cannot concatenate object of type '<class 'numpy.float64'>'; only Series and DataFrame objs are valid

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-14-ef771c688be7> in <module>
----> 1 df.agg(["mean", perc_fun(10)])

~/.local/lib/python3.7/site-packages/pandas/core/frame.py in aggregate(self, func, axis, *args, **kwargs)
   6704         result = None
   6705         try:
-> 6706             result, how = self._aggregate(func, axis=axis, *args, **kwargs)
   6707         except TypeError:
   6708             pass

~/.local/lib/python3.7/site-packages/pandas/core/frame.py in _aggregate(self, arg, axis, *args, **kwargs)
   6718             result = result.T if result is not None else result
   6719             return result, how
-> 6720         return super()._aggregate(arg, *args, **kwargs)
   6721 
   6722     agg = aggregate

~/.local/lib/python3.7/site-packages/pandas/core/base.py in _aggregate(self, arg, *args, **kwargs)
    484         elif is_list_like(arg):
    485             # we require a list, but not an 'str'
--> 486             return self._aggregate_multiple_funcs(arg, _axis=_axis), None
    487         else:
    488             result = None

~/.local/lib/python3.7/site-packages/pandas/core/base.py in _aggregate_multiple_funcs(self, arg, _axis)
    530                 colg = self._gotitem(col, ndim=1, subset=obj.iloc[:, index])
    531                 try:
--> 532                     new_res = colg.aggregate(arg)
    533                 except (TypeError, DataError):
    534                     pass

~/.local/lib/python3.7/site-packages/pandas/core/series.py in aggregate(self, func, axis, *args, **kwargs)
   3686         # Validate the axis parameter
   3687         self._get_axis_number(axis)
-> 3688         result, how = self._aggregate(func, *args, **kwargs)
   3689         if result is None:
   3690 

~/.local/lib/python3.7/site-packages/pandas/core/base.py in _aggregate(self, arg, *args, **kwargs)
    484         elif is_list_like(arg):
    485             # we require a list, but not an 'str'
--> 486             return self._aggregate_multiple_funcs(arg, _axis=_axis), None
    487         else:
    488             result = None

~/.local/lib/python3.7/site-packages/pandas/core/base.py in _aggregate_multiple_funcs(self, arg, _axis)
    562             result = Series(results, index=keys, name=self.name)
    563             if is_nested_object(result):
--> 564                 raise ValueError("cannot combine transform and aggregation operations")
    565             return result
    566 

ValueError: cannot combine transform and aggregation operations

</details>

#### Problem description

The same code produced a different error in 0.24 so I assume some work has been done, but the error message is not very informative and I really think this should just work by inserting the appropriate 1.4 and 1.5 values

I couldn't find any related issues, if no one has experience with this, I will look into .agg code


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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.2.1-1.el7.elrepo.x86_64
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2018.4
dateutil         : 2.7.3
pip              : 19.3.1
setuptools       : 41.4.0
Cython           : None
pytest           : 4.1.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.1 (dt dec pq3 ext lo64)
jinja2           : 2.10
IPython          : 7.9.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 4.1.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.2.8
tables           : None
tabulate         : 0.8.6
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
