BUG: converting null timedelta to int with astype() changes NaT to -9223372036854775808

[sfc-gh-mvashishtha]

Pandas version checks

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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

print(pd.DataFrame([pd.Timedelta(1), None]).astype(int).iloc[1, 0])

Issue Description

astype(int) converts missing values in a timedelta series to -9223372036854775808.

Expected Behavior

I'd expect the same error I get from calling astype(int) on a float dataframe with a null:

import pandas as pd

pd.DataFrame([1, None]).astype(int)

The error is IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer.

Installed Versions

INSTALLED VERSIONS
------------------
commit                : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140
python                : 3.9.18.final.0
python-bits           : 64
OS                    : Darwin
OS-release            : 23.6.0
Version               : Darwin Kernel Version 23.6.0: Mon Jul 29 21:13:04 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T6020
machine               : arm64
processor             : arm
byteorder             : little
LC_ALL                : None
LANG                  : en_US.UTF-8
LOCALE                : en_US.UTF-8

pandas                : 2.2.2
numpy                 : 1.26.3
pytz                  : 2023.3.post1
dateutil              : 2.8.2
setuptools            : 68.2.2
pip                   : 23.3.1
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               : 8.18.1
pandas_datareader     : None
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : None
bottleneck            : None
dataframe-api-compat  : None
fastparquet           : None
fsspec                : None
gcsfs                 : None
matplotlib            : None
numba                 : None
numexpr               : None
odfpy                 : None
openpyxl              : None
pandas_gbq            : None
pyarrow               : None
pyreadstat            : None
python-calamine       : None
pyxlsb                : None
s3fs                  : None
scipy                 : None
sqlalchemy            : None
tables                : None
tabulate              : None
xarray                : None
xlrd                  : None
zstandard             : None
tzdata                : 2023.4
qtpy                  : None
pyqt5                 : None

[rhshadrach]

None and NaN cannot be stored in an array of dtype int. When you say the expected result is pd.DataFrame([1, None]) are you saying that you expect .astype(int) to give a float dtype back instead?

[sfc-gh-mvashishtha]

None and NaN cannot be stored in an array of dtype int.

I see. Then I think I'd expect the same error I get from calling astype(int) on a float dataframe with a null:

import pandas as pd

pd.DataFrame([1, None]).astype(int)

The error is IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer.

I updated the "expected behavior" section of the original issue.