BUG: DatetimeIndex.to_period().to_timestamp() forgets freq value · Issue #38885 · pandas-dev/pandas (original) (raw)

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Code Sample, a copy-pastable example

pd.date_range(start='1/1/2018 00:00:00', end='2/1/2018 00:01:00', freq="MS") DatetimeIndex(['2018-01-01', '2018-02-01'], dtype='datetime64[ns]', freq='MS')

pd.date_range(start='1/1/2018 00:00:00', end='2/1/2018 00:01:00', freq="MS").to_period().to_timestamp() DatetimeIndex(['2018-01-01', '2018-02-01'], dtype='datetime64[ns]', freq=None)

Problem description

Why is freq=None here in the end? Is it possible to make conversion between DatetimeIndex and PeriodIndex more reliable in any way? How can I know which freq values are not able to be converted from PeriodIndex into DatetimeIndex?

Expected Output:

I would expect to have the same freq value after doing .to_period().to_timestamp().

pd.date_range(start='1/1/2018 00:00:00', end='2/1/2018 00:01:00', freq="MS").to_period().to_timestamp() DatetimeIndex(['2018-01-01', '2018-02-01'], dtype='datetime64[ns]', freq="MS")

Output of pd.show_versions()

<details>

INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.7.9.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : AMD64 Family 21 Model 112 Stepping 0, AuthenticAMD
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.2.0
numpy            : 1.19.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.3.1
setuptools       : 51.0.0.post20201207
Cython           : 0.29.17
pytest           : 6.1.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.4
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.4
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.50.1
</details>