series.replace with empty dictlike raises ValueError: not enough values to unpack
#### Problem description

`DataFrame.replace` and `Series.replace` fail unceremoniously on an empty Series or dict argument; I would expect it to simply do nothing.

While there is a fair bit of type-based wizardry going on in this function, I don't suppose there is any actual ambiguity in how this edge case should behave?

#### Code Sample, a copy-pastable example if possible

```python
from pandas import Series
s = Series([0,0,1,1,2,2])
print(s.replace(Series([7,7])).tolist())
print(s.replace(Series([7])).tolist())
print(s.replace(Series([])).tolist())
```

#### Output

```text
[7, 7, 7, 7, 2, 2]
[7, 7, 1, 1, 2, 2]
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-82-d889d2100216> in <module>()
      3 print(s.replace(Series([7,7])).tolist())
      4 print(s.replace(Series([7])).tolist())
----> 5 print(s.replace(Series([])).tolist())

/usr/local/lib/python3.5/dist-packages/pandas-0.19.2-py3.5-linux-x86_64.egg/pandas/core/generic.py in replace(self, to_replace, value, inplace, limit, regex, method, axis)
   3438 
   3439             items = list(compat.iteritems(to_replace))
-> 3440             keys, values = zip(*items)
   3441 
   3442             are_mappings = [is_dict_like(v) for v in values]

ValueError: not enough values to unpack (expected 2, got 0)
```

#### Expected Output

```
[7, 7, 7, 7, 2, 2]
[7, 7, 1, 1, 2, 2]
[0, 0, 1, 1, 2, 2]
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-59-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.2
nose: None
pip: 8.1.2
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.0
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.2.0
tables: None
numexpr: 2.6.2
matplotlib: 1.5.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: 0.7.3
lxml: None
bs4: 4.4.1
html5lib: 0.999
httplib2: 0.9.1
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
</details>
