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BUG: PeriodIndex.to_datetime inconsistent with its docstring #59371

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MarcoGorelli opened this issue Jul 31, 2024 · 2 comments · May be fixed by #60350
Open
3 tasks done

BUG: PeriodIndex.to_datetime inconsistent with its docstring #59371

MarcoGorelli opened this issue Jul 31, 2024 · 2 comments · May be fixed by #60350
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@MarcoGorelli
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Pandas version checks

  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
pd.period_range('2000', periods=3, freq='M').to_timestamp('M')

Issue Description

The docs say

Cast to DatetimeIndex of timestamps, at beginning of period.

A Period(freq='M') starts at the beginning of the month, and ends on the last moment before the next month:

In [7]: pd.Period('2000', freq='M').start_time
Out[7]: Timestamp('2000-01-01 00:00:00')

In [8]: pd.Period('2000', freq='M').end_time
Out[8]: Timestamp('2000-01-31 23:59:59.999999999')

Expected Behavior

So, I'd have expected the above to output

DatetimeIndex(['2000-01-01', '2000-02-01', '2000-03-01'], dtype='datetime64[ns]', freq='MS')

Instead, we get

DatetimeIndex(['2000-01-31', '2000-02-29', '2000-03-31'], dtype='datetime64[ns]', freq='ME')

This looks odd. But, it's also been like that since as far back as I tested (i.e. pandas 0.25.3 😱 )

>>> import pandas as pd
>>> pd.period_range('2000', periods=3, freq='M').to_timestamp('M')
DatetimeIndex(['2000-01-31', '2000-02-29', '2000-03-31'], dtype='datetime64[ns]', freq='M')
>>> pd.__version__
'0.25.3'

Urgh, now what.

Splitting this off from #58974

Installed Versions

INSTALLED VERSIONS

commit : b552dc9
python : 3.10.12
python-bits : 64
OS : Linux
OS-release : 5.15.153.1-microsoft-standard-WSL2
Version : #1 SMP Fri Mar 29 23:14:13 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 3.0.0.dev0+618.gb552dc95c9
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
pip : 24.0
Cython : 3.0.9
sphinx : 7.2.6
IPython : 8.22.2
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : 1.3.8
fastparquet : 2024.2.0
fsspec : 2024.3.1
html5lib : 1.1
hypothesis : 6.99.13
gcsfs : 2024.3.1
jinja2 : 3.1.3
lxml.etree : 5.1.0
matplotlib : 3.8.3
numba : 0.59.1
numexpr : 2.9.0
odfpy : None
openpyxl : 3.1.2
psycopg2 : 2.9.9
pymysql : 1.4.6
pyarrow : 16.1.0
pyreadstat : 1.2.7
pytest : 8.1.1
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2024.3.1
scipy : 1.12.0
sqlalchemy : 2.0.29
tables : 3.9.2
tabulate : 0.9.0
xarray : 2024.2.0
xlrd : 2.0.1
xlsxwriter : 3.2.0
zstandard : 0.22.0
tzdata : 2024.1
qtpy : None
pyqt5 : None
@MarcoGorelli MarcoGorelli added Bug Needs Triage Issue that has not been reviewed by a pandas team member Frequency DateOffsets and removed Needs Triage Issue that has not been reviewed by a pandas team member labels Jul 31, 2024
@MarcoGorelli
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I think this should be treated as a bug and just fixed in 3.0? will investigate more closely

@aram-cinnamon
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take

@MarcoGorelli MarcoGorelli mentioned this issue Aug 5, 2024
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@aram-cinnamon aram-cinnamon mentioned this issue Oct 3, 2024
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@aram-cinnamon aram-cinnamon linked a pull request Nov 17, 2024 that will close this issue
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