BUG: df.replace() 
- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the latest version of pandas.

- [X] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd

df = pd.DataFrame.from_dict(
    {
        'a_original': ['w', 'x', 'y', 'z', 'w', 'x', 'y', 'z'],
        'a_expected': ['w', 'x', 'y', 'z', 'w', 'x', 'y', 'z'],
        'a_result': ['w', 'x', 'y', 'z', 'w', 'x', 'y', 'z'],
        'b_original': ['w', 'x', 'y', 'z', 'z', 'y', 'x', 'w'],
        'b_expected': ['w', 'x', 'y', 'z', 'z', 'y', 'x', 'w'],
        'b_result': ['w', 'x', 'y', 'z', 'z', 'y', 'x', 'w']
    }
)

# Produces expectation.
df.replace(
    {column: {replace: None for replace in ['x', 'z']} for column in ['a_expected', 'b_expected']},
    inplace=True
)

# Does not produce expectation.
df.replace(
    {column: ['x', 'z'] for column in ['a_result', 'b_result']},
    {column: None for column in ['a_result', 'b_result']},
    inplace=True
)

>>
  a_original a_expected a_result b_original b_expected b_result
0          w          w        w          w          w        w
1          x       None        w          x       None        w
2          y          y        y          y          y        y
3          z       None        y          z       None        y
4          w          w        w          z       None        y
5          x       None        w          y          y        y
6          y          y        y          x       None        y
7          z       None        y          w          w        w
```

#### Problem description
`df.replace()` has multiple ways to define which values in which columns ought to be replaced. I expected the two uses of `df.replace()` above to be equivalent, but the second does not replace the values "x" and "z" in the declared columns with `None`. Instead, some form of filling/padding is used.

#### Expected Output
The second instance of `df.replace()` should be the same as the first; all instances of "x" and "z" should be replaced with `None`, but there seems to be a default usage of `method` underneath; this result remains the case, no matter what is entered into `method`.

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

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.112+
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.5
numpy            : 1.18.5
pytz             : 2018.9
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 49.2.0
Cython           : 0.29.21
pytest           : 3.6.4
hypothesis       : None
sphinx           : 1.8.5
blosc            : None
feather          : 0.4.1
xlsxwriter       : 1.3.3
lxml.etree       : 4.2.6
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 5.5.0
pandas_datareader: 0.8.1
bs4              : 4.6.3
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.2.6
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 2.5.9
pandas_gbq       : 0.11.0
pyarrow          : 1.0.0
pytables         : None
pytest           : 3.6.4
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.4.1
sqlalchemy       : 1.3.18
tables           : 3.4.4
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.1.0
xlwt             : 1.3.0
xlsxwriter       : 1.3.3
numba            : 0.48.0

</details>
