BUG: Series.astype is unable to handle NaN

[ingted]

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• 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({"a":[2.0, np.nan, 1.0]})
df = df.astype(object)
def iif(a, b, c):
    if a:
        return b
    else:
        return c

df["a"].astype(object).apply(lambda r: iif(np.isnan(r),None,r)).astype(object).apply(lambda r: iif(np.isnan(r),None,r))
df

Issue Description

The result is:

0    2.0
1    NaN
2    1.0

Expected Behavior

The result should be:

0    2.0
1    None
2    1.0

I checked BUG: Replacing NaN with None in Pandas 1.3 does not work
But it seems astype doesn't work here.

Installed Versions

INSTALLED VERSIONS

commit : 06d2301
python : 3.8.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 79 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.950

pandas : 1.4.1
numpy : 1.22.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.1.1
setuptools : 56.0.0
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 : 8.1.1
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.8.0
sqlalchemy : 1.4.32
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None

[ingted]

However,

df.where(pd.notnull(df), None)

could lead to

0    2.0
1    None
2    1.0

[rhshadrach]

Thanks for the report! I wonder if apply is coercing the result into a numeric dtype. I would agree this is not expected, further investigations and PRs to fix are welcome!

[kapiliyer]

take