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Yah, this is a Hard Problem. The .freq is actually wrong even before the .tz_convert. This is due to a before-my-time "we'll just pretend" in the date_range implementation (grep for "We break Day arithmetic"). xref #41943 and links there, attempted implementation #44364.
Day needs to be changed to mean day-respecting-dst, and users specifically wanting 24 hours should use "24h". We determined a while back that there wasn't a nice way to do this as a deprecation, so it would have to be a breaking change in a major release (it is listed in #44823). I tried last month to do this just under the wire for the RC but found it was not a weekend-sized problem.
I'd love to see this addressed for 3.0, am kind of hoping @mroeschke will make another attempt at implementing. I suspect this would solve many of the extant 'timezones' issues.
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Reproducible Example
Issue Description
The above returns:
The frequency is not constant (it is once 23h), and thus should freq not be "D".
Expected Behavior
Installed Versions
INSTALLED VERSIONS
commit : 2e218d1
python : 3.10.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Belgium.1252
pandas : 1.5.3
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.2.0
pip : 23.0
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.8
lxml.etree : 4.9.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.6
brotli : None
fastparquet : 2023.2.0
fsspec : 2021.11.0
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2021.11.0
scipy : 1.10.0
snappy : None
sqlalchemy : None
tables : None
tabulate : 0.8.10
xarray : 2022.12.0
xlrd : None
xlwt : None
zstandard : None
tzdata : None
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