BUG: inconsistency in freq of DatetimeIndex when converting PeriodIndex.to_timestamp #56213
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
import pandas as pd
per = pd.PeriodIndex(['2012-01', '2012-04', '2012-07'], dtype='period[Q]')
per.to_timestamp(how='start')
per = pd.PeriodIndex(['2012-01', '2012-04'], dtype='period[Q]')
per.to_timestamp(how='start')
per = pd.PeriodIndex(['2012-01', '2012-02', '2012-03'], dtype='period[M]')
per.to_timestamp(how='start')
per = pd.PeriodIndex(['2012-01', '2012-02'], dtype='period[M]')
per.to_timestamp(how='start')Issue Description
this outputs
per = pd.PeriodIndex(['2012-01', '2012-04', '2012-07'], dtype='period[Q]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-04-01', '2012-07-01'], dtype='datetime64[ns]', freq='QS-OCT')
per = pd.PeriodIndex(['2012-01', '2012-04'], dtype='period[Q]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-04-01'], dtype='datetime64[ns]', freq=None)
per = pd.PeriodIndex(['2012-01', '2012-02', '2012-03'], dtype='period[M]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-02-01', '2012-03-01'], dtype='datetime64[ns]', freq='MS')
per = pd.PeriodIndex(['2012-01', '2012-02'], dtype='period[M]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-02-01'], dtype='datetime64[ns]', freq=None)
Expected Behavior
during conversion PeriodIndex.to_timestamp freq in DatetimeIndex unexpectedly depends on len of data. Shouldn't freqs in all examples above be equal 'QS-OCT' and 'MS', but not None?
per = pd.PeriodIndex(['2012-01', '2012-04'], dtype='period[Q]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-04-01'], dtype='datetime64[ns]', freq='QS-OCT')
per = pd.PeriodIndex(['2012-01', '2012-02'], dtype='period[M]')
per.to_timestamp(how='start')
DatetimeIndex(['2012-01-01', '2012-02-01'], dtype='datetime64[ns]', freq='MS')
Installed Versions
INSTALLED VERSIONS
commit : b7a2207
python : 3.10.13.final.0
python-bits : 64
OS : Linux
OS-release : 4.19.0-22-amd64
Version : #1 SMP Debian 4.19.260-1 (2022-09-29)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 2.1.0.dev0+1330.gb7a220731e.dirty
numpy : 1.26.0
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.1.2
pip : 23.3.1
Cython : 3.0.5
pytest : 7.4.3
hypothesis : 6.89.0
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.1.9
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.7
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : 2023.10.1
fsspec : 2023.10.0
gcsfs : 2023.10.0
matplotlib : 3.8.1
numba : 0.58.1
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 14.0.1
pyreadstat : 1.2.4
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.10.0
scipy : 1.11.3
sqlalchemy : 2.0.23
tables : 3.9.1
tabulate : 0.9.0
xarray : 2023.11.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2023.3
qtpy : None
pyqt5 : None