Series.combine() with a scalar only works if function is compatible with (vec, scalar) operation
#### Code Sample, a copy-pastable example if possible

```python
In [1]: import pandas as pd

In [2]: s = pd.Series([i*10 for i in range(5)])
   ...: s
   ...:
Out[2]:
0     0
1    10
2    20
3    30
4    40
dtype: int64

In [3]: s.combine(3, lambda x,y: x + y)
Out[3]:
0     3
1    13
2    23
3    33
4    43
dtype: int64

In [4]: s.combine(22, lambda x,y: min(x,y))
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-b2ac1f5a4fa4> in <module>()
----> 1 s.combine(22, lambda x,y: min(x,y))

C:\Anaconda3\lib\site-packages\pandas\core\series.py in combine(self, other, func, fill_value)
   2240             new_index = self.index
   2241             with np.errstate(all='ignore'):
-> 2242                 new_values = func(self._values, other)
   2243             new_name = self.name
   2244         return self._constructor(new_values, index=new_index, name=new_name)

<ipython-input-4-b2ac1f5a4fa4> in <lambda>(x, y)
----> 1 s.combine(22, lambda x,y: min(x,y))

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

In [5]:  s.combine(pd.Series([22,22,22,22,22]), lambda x,y: min(x,y))
Out[5]:
0     0
1    10
2    20
3    22
4    22
dtype: int64
```
#### Problem description

In the case of using `Series.combine()` with a scalar argument, it only works if the corresponding function `func` supports `func(Series, scalar)`.  Implementation should always use an element-by-element implementation.  The results of `[3]` and `[5]` are expected, but `[4]` should still work.

#### Expected Output

For `[4]`, it should look like the output of `[5]` above.


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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
