Description
Pandas version checks
-
I have checked that this issue has not already been reported.
-
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
df = pd.DataFrame({'timestamp': [pd.Timestamp('2024-01-01T00:00', tz='UTC')], 'category': ['A'], 'value': [100]})
df[df.category == "C"].pivot_table(index="category", columns="value", values="timestamp")
Issue Description
This raises an error TypeError: Cannot interpret 'datetime64[ns, UTC]' as a data type
Expected Behavior
It should return an empty DataFrame.
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.12.3.final.0
python-bits : 64
OS : Darwin
OS-release : 23.5.0
Version : Darwin Kernel Version 23.5.0: Wed May 1 20:14:38 PDT 2024; root:xnu-10063.121.3~5/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 69.5.1
pip : 24.0
Cython : None
pytest : 8.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 5.2.1
html5lib : None
pymysql : None
psycopg2 : 2.9.9
jinja2 : 3.1.4
IPython : 8.23.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.5.0
gcsfs : None
matplotlib : 3.8.4
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.0
pandas_gbq : None
pyarrow : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : 2024.5.0
scipy : None
sqlalchemy : 2.0.30
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None