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Reproducible Example

import pandas as pd
pd.Series(pd.NaT).dt.tz_localize("UTC").to_numpy("datetime64")

> TypeError: 'float' object cannot be interpreted as an integer

Issue Description

tz-aware series with NaT raises exception on .to_numpy("datetime64")

Expected Behavior

Expect same behavior as a tz-naive series, e.g.

pd.Series(pd.NaT).to_numpy("datetime64")

numpy.datetime64('NaT')

Installed Versions

INSTALLED VERSIONS ------------------ commit : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140 python : 3.11.6.final.0 python-bits : 64 OS : Linux OS-release : 5.10.0-29-cloud-amd64 Version : #1 SMP Debian 5.10.216-1 (2024-05-03) machine : x86_64 processor : byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.2.2 numpy : 1.26.4 pytz : 2022.7.1 dateutil : 2.9.0.post0 setuptools : 69.2.0 pip : 24.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.4 IPython : 8.23.0 pandas_datareader : None adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : None bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : 2024.6.1 gcsfs : 2024.6.1 matplotlib : 3.9.0 numba : 0.58.1 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 14.0.2 pyreadstat : None python-calamine : None pyxlsb : None s3fs : None scipy : 1.13.1 sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None zstandard : None tzdata : 2024.1 qtpy : None pyqt5 : None

Comment From: yuanx749

Specify "datetime64[ns]" instead of "datetime64" would work.

Comment From: rhshadrach

Thanks for the report and @yuanx749 for the work around. But it does seem to me that this should work without [ns] as well. Further investigations and PRs to fix are welcome!

Comment From: tomasmacieira

take