BUG: pd.fillna(np.nan, inplace=True) replaces values which are not None when using datetime dtype

[adnapPanda]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import numpy as np

df = pd.DataFrame(
    {
        "date1": pd.to_datetime(["2018-05-30", "2018-06-30", None]),
        "date2": pd.to_datetime(
            [
                None,
                "2018-08-30",
                "2018-09-30",
            ]
        ),
        "date3": pd.to_datetime(
            [
                "2018-08-30",
                None,
                "2018-10-30",
            ]
        ),
    }
)

       date1      date2      date3
0 2018-05-30        NaT 2018-08-30
1 2018-06-30 2018-08-30        NaT
2        NaT 2018-09-30 2018-10-30

df.fillna(np.nan, inplace=True)

       date1      date2      date3
0 2018-05-30        NaT        NaT
1        NaT 2018-08-30        NaT
2        NaT        NaT 2018-10-30

Issue Description

When using the pandas method fillna() and specifying fillna(np.nan, inplace=True), values which are not None are replaced with NaT when using the datetime dtype. When the inplace=True argument is left out and the result of fillna(np.nan) is assigned to a variable, then the expected output is recieved.

Expected Behavior

The expected output is the following:

df.fillna(np.nan, inplace=True)

       date1      date2      date3
0 2018-05-30        NaT 2018-08-30
1 2018-06-30 2018-08-30        NaT
2        NaT 2018-09-30 2018-10-30

Installed Versions

commit : 87cfe4e
python : 3.10.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 151 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Netherlands.1252
pandas : 1.5.0
numpy : 1.23.3
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 63.2.0
pip : 22.2.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.0
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[phofl]

Hi, thanks for your report.

commit 769fc54897953d366d573d4e45cf13177a5f582b
Author: jbrockmendel <jbrockmendel@gmail.com>
Date:   Thu Feb 10 18:01:53 2022 -0800

    REF: dispatch Block.fillna to putmask/where (#45911)

[MarcoGorelli]

Hey @adnapPanda

Thanks for having reported this - there's now a release candidate for pandas 2.0.0, which you can install with

mamba install -c conda-forge/label/pandas_rc pandas==2.0.0rc0

or

python -m pip install --upgrade --pre pandas==2.0.0rc0

If you try it out and report bugs, then we can fix them before the final 2.0.0 release