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Reproducible Example

pd.period_range("2020", periods=2, freq="M").to_timestamp(to_offset("ME"))
# Outputs DatetimeIndex(['2020-01-31', '2020-02-29'], dtype='datetime64[ns]', freq=None)

pd.period_range("2020", periods=3, freq="M").to_timestamp(to_offset("ME"))
# Outputs DatetimeIndex(['2020-01-31', '2020-02-29', '2020-03-31'], dtype='datetime64[ns]', freq='ME') Wrong frequency

pd.period_range("2020", periods=2, freq="M").to_timestamp("ME") # Fails

pd.period_range("2020", periods=3, freq="M").to_timestamp("ME") # Fails

Issue Description

Related to #56213

Expected Behavior

All of these four lines should return a datetindex with 2ME as frequency.

I suppose that the the frequency term in to_timestamp is ignored and the frequency is directly inferred.

Installed Versions

INSTALLED VERSIONS ------------------ commit : bdc79c146c2e32f2cab629be240f01658cfb6cc2 python : 3.10.13.final.0 python-bits : 64 OS : Darwin OS-release : 23.2.0 Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:59:33 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T8112 machine : arm64 processor : arm byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.2.1 numpy : 1.26.4 pytz : 2024.1 dateutil : 2.8.2 setuptools : 68.2.2 pip : 23.3.1 Cython : 3.0.8 pytest : 7.4.0 hypothesis : None sphinx : 7.2.6 blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.3 IPython : 8.21.0 pandas_datareader : None adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : 4.12.3 bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : 2023.12.2 gcsfs : None matplotlib : 3.8.2 numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 15.0.0 pyreadstat : None python-calamine : None pyxlsb : None s3fs : None scipy : 1.10.1 sqlalchemy : 2.0.28 tables : None tabulate : None xarray : 2024.1.1 xlrd : None zstandard : None tzdata : 2023.4 qtpy : None pyqt5 : None

Comment From: kvnwng11

take