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
.Issue Description
I'm testing a pull-request on pycaret pycaret/pycaret#3857 to support new scikit-learn 1.4, and new pandas 2.2.0 also.
I fixed/removed deprecated ALIAS of time frequencies, as you can see here: pycaret/pycaret@039f159
However as i can see in pandas doccumentation of pandas 2.2 https://pandas.pydata.org/docs/whatsnew/v2.2.0.html#deprecate-aliases-m-q-y-etc-in-favour-of-me-qe-ye-etc-for-offsets, the alias M is changed to ME, but something is wrong because i receive an error because ME is in use... i give you an picture of my vscode:
As you can see, have an error ValueError: Invalid frequency: ME, failed to parse with error message: ValueError("for Period, please use 'M' instead of 'ME'")
but i have pandas 2.2 as you can see (i used terminal to show pandas version)
Expected Behavior
No errors
Installed Versions
INSTALLED VERSIONS
commit : f538741
python : 3.10.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : pt_BR.UTF-8
LOCALE : Portuguese_Portugal.1252
pandas : 2.2.0
numpy : 1.26.3
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 23.3.2
Cython : 0.29.36
pytest : 7.4.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.20.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2023.10.0
gcsfs : None
matplotlib : 3.8.2
numba : 0.58.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None