Pandas version checks

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  • [ ] 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 : 87cfe4e38bafe7300a6003a1d18bd80f3f77c763 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

Comment From: 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)

Comment From: 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