BUG: Series.replace with to_replace dict and value=None, nonsensical error message

[d-rams]

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Reproducible Example

import pandas as pd
s = pd.Series([1,2,3,4])
s.replace(to_replace={3:33}, value=None)

Issue Description

import pandas as pd
s = pd.Series([1,2,3,4])
s.replace(to_replace={3:33}, value=7)

yields the error as expected:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/drams/anaconda3/envs/plombier-dev/lib/python3.10/site-packages/pandas/core/series.py", line 4960, in replace
    return super().replace(
  File "/Users/drams/anaconda3/envs/plombier-dev/lib/python3.10/site-packages/pandas/core/generic.py", line 6685, in replace
    raise ValueError(
ValueError: Series.replace cannot use dict-like to_replace and non-None value

However,

import pandas as pd
s = pd.Series([1,2,3,4])
s.replace(to_replace={3:33}, value=None)

yields exactly the same error

Expected Behavior

I suspect this change occurred because we now treat None in the value field explicitly. However, the error message makes no sense anymore. I believe the expected behavior is that we get an error telling us that even None is no longer allowed for value when using a dict in to_replace.

Installed Versions

INSTALLED VERSIONS

commit : 06d2301
python : 3.10.2.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Tue Oct 12 18:33:42 PDT 2021; root:xnu-7195.141.8~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.1
numpy : 1.22.2
pytz : 2021.3
dateutil : 2.8.2
pip : 22.0.3
setuptools : 60.9.1
Cython : None
pytest : 7.0.1
hypothesis : 6.36.2
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : 2022.01.0
gcsfs : None
matplotlib : None
numba : None
numexpr : 2.8.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : 2022.01.0
scipy : None
sqlalchemy : 1.4.31
tables : 3.7.0
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
zstandard : None

[Kyrpel]

take

[alainrafiki]

The error message may need to be improved for clarity.

df = df1.replace(to_replace=dictionaryvar, value=None, inplace=False) resulted in the same error for me as well:

ValueError: Series.replace cannot use dict-like to_replace and non-None value