BUG: dataframe.replace({np.nan: None}) failed when replaced even number of times
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [x] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

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


def check_nan(df):
    for entry in df.to_dict(orient='records'):
        if any([isinstance(v, float) and np.isnan(v) for v in entry.values()]):
            return True

    return False


def generate_df():
    return pd.DataFrame(dict(age=[5, 6, np.NaN],
                             born=[pd.NaT, pd.Timestamp('1939-05-27'),
                                   pd.Timestamp('1940-04-25')],
                             name=['Alfred', 'Batman', ''],
                             toy=[None, 'Batmobile', 'Joker']))


def where_not_working():
    df = generate_df()
    df = df.where((pd.notnull(df)), None)
    print('where not working', check_nan(df))

def replace_working():
    df = generate_df()
    df = df.replace({np.nan: None})
    print('replace working', check_nan(df))

def replace_twice_not_working():
    df = generate_df()
    df = df.replace({np.nan: None})
    df = df.replace({np.nan: None})
    print('replace twice not working', check_nan(df))

def replace_odd_num_working():
    df = generate_df()
    df = df.replace({np.nan: None})
    df = df.replace({np.nan: None})
    df = df.replace({np.nan: None})
    print('replace three times working', check_nan(df))


where_not_working()
replace_working()
replace_twice_not_working()
replace_odd_num_working()
```


### Issue Description

As shown in the example above:
dataframe.replace({np.nan: None}) works when it's applied to a dataframe once, 3 times, but not working (or "reverse" the change) when run twice, 4 times, etc.


### Expected Behavior

It should consistently have the result dataframe containing no np.nan, doesn't matter how many replace attempts have been made.

### Installed Versions

INSTALLED VERSIONS
------------------
commit           : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python           : 3.8.12.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.18.0-240.1.1.el8_3.x86_64
Version          : #1 SMP Fri Oct 16 13:36:46 EDT 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.3.4
numpy            : 1.21.2
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.2.4
setuptools       : 58.0.4
Cython           : None
pytest           : 6.2.4
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.2
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : 1.3.2
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.9
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.1
sqlalchemy       : 1.4.22
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None