Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
timestamp = pd.to_datetime("2023-01-01", utc=True)
df = pd.DataFrame(
{
"index": pd.Series([pd.NaT, timestamp]),
"value": pd.Series([0, 1]),
}
).set_index("index")
assert df.loc[pd.Series([pd.NaT, timestamp, timestamp], dtype=df.index.dtype),][
"value"
].tolist() == [0, 1, 1]
# The line bellow throws KeyError
# None of [DatetimeIndex(['NaT'], dtype='datetime64[ns]', name='index', freq=None)] are in the [index]
# But you'd expect [0]
assert df.loc[pd.Series([pd.NaT], dtype=df.index.dtype),]["value"].tolist() == [0]Issue Description
If pd.NaT is in my df index, I should be able to get df.loc[pa.NaT, ].
This works in most cases, for example tz-naive, or if the argument of loc is a mix of NaT and valid values.
But it stops working if the index is tz-aware and the argument to loc is all NaT.
Expected Behavior
df.loc[pd.Series([pd.NaT], dtype=df.index.dtype),]["value"].tolist() should return [0]
Installed Versions
INSTALLED VERSIONS
commit : 0f43794
python : 3.10.11.final.0
python-bits : 64
OS : Darwin
OS-release : 22.6.0
Version : Darwin Kernel Version 22.6.0: Wed Jul 5 22:22:05 PDT 2023; root:xnu-8796.141.3~6/RELEASE_ARM64_T6000
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 2.0.3
numpy : 1.24.2
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.3.1
pip : 23.2.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : 2.9.5
jinja2 : 3.1.2
IPython : 8.14.0
pandas_datareader: 0.9.0
bs4 : 4.12.2
bottleneck : None
brotli : None
fastparquet : None
fsspec : 2023.6.0
gcsfs : None
matplotlib : 3.6.0
numba : None
numexpr : 2.8.4
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 12.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2023.6.0
scipy : 1.10.1
snappy : None
sqlalchemy : 2.0.9
tables : None
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : 2.2.0
pyqt5 : None