pandas.DataFrame.replace appears to replace multiple times
#### Here's an easy to produce example:

```python
df = pd.DataFrame({'A': ['a', 'a', 'b']})
dct = {'a': 'b', 'b': 'hello'}
```
#### Problem description

When I use `df.A.replace(dct)`, it seems as though the replacement is being applied recursively, and updating until no matches can be found.  Here is the output I am currently getting:

```python
>>> df.A.replace(dct)
0    hello
1    hello
2    hello
Name: A, dtype: object
```

As you can see it seems like `a` is replaced by `b` is replaced by `hello`, instead of the single replacement I would expect.  I looked through the documentation for `replace`, and saw nothing that claimed this was intended.

#### Expected Output

I would expect the output to be the same as `df.A.map(dct)`

```python
0        b
1        b
2    hello
Name: A, dtype: object
```

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

<details>

```

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.4
pytest: 2.9.2
pip: 10.0.1
setuptools: 39.0.1
Cython: None
numpy: 1.15.0
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: 0.9.3
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.8
pymysql: None
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>

```
