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BUG: Period constructor raises instead of ignoring when passing a string with extra precision(pico, femto, etc.) #50417

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Merged
merged 5 commits into from
Jan 16, 2023
Merged

BUG: Period constructor raises instead of ignoring when passing a string with extra precision(pico, femto, etc.) #50417

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89a5b68
TST: Add test for Period construction from str with zero nanos
lithomas1 Dec 23, 2022
20b6b13
BUG: Period would raise a KeyError when given a string with extra pre…
lithomas1 Dec 23, 2022
773df4f
Merge branch 'main' into test-period-zero-nanos
lithomas1 Dec 30, 2022
1e67122
Update parsing.pyx
lithomas1 Jan 3, 2023
ee250e5
Merge branch 'main' into test-period-zero-nanos
lithomas1 Jan 11, 2023
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v2.0.0.rst
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Expand Up @@ -921,7 +921,7 @@ Period
^^^^^^
- Bug in :meth:`Period.strftime` and :meth:`PeriodIndex.strftime`, raising ``UnicodeDecodeError`` when a locale-specific directive was passed (:issue:`46319`)
- Bug in adding a :class:`Period` object to an array of :class:`DateOffset` objects incorrectly raising ``TypeError`` (:issue:`50162`)
-
- Bug in :class:`Period` where passing a string with finer resolution than nanosecond would result in a ``KeyError`` instead of dropping the extra precision (:issue:`50417`)

Plotting
^^^^^^^^
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8 changes: 7 additions & 1 deletion pandas/_libs/tslibs/parsing.pyx
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Expand Up @@ -386,7 +386,7 @@ cdef parse_datetime_string_with_reso(
&out_tzoffset, False
)
if not string_to_dts_failed:
if dts.ps != 0 or out_local:
if out_bestunit == NPY_DATETIMEUNIT.NPY_FR_ns or out_local:
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makes sense. to be totally correct we might need to check for ps, fs, as?

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Good point. What should be the error message we raise, or should we silently ignore?

On 1.5.2, doing pd.Period("1970/01/01 00:00:00.000000000111") gives me

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pandas/_libs/tslibs/period.pyx", line 2579, in pandas._libs.tslibs.period.Period.__new__
  File "pandas/_libs/tslibs/parsing.pyx", line 369, in pandas._libs.tslibs.parsing.parse_time_string
  File "pandas/_libs/tslibs/parsing.pyx", line 431, in pandas._libs.tslibs.parsing.parse_datetime_string_with_reso
KeyError: 11

Timestamp seems to ignore the extra precision, so maybe we should match that here?

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definitely better than the status quo. it might be reasonable to have Timestamp warn/raise instead of silently truncating, but thats out of scope.

# TODO: the not-out_local case we could do without Timestamp;
# avoid circular import
from pandas import Timestamp
Expand All @@ -395,6 +395,12 @@ cdef parse_datetime_string_with_reso(
parsed = datetime(
dts.year, dts.month, dts.day, dts.hour, dts.min, dts.sec, dts.us
)
# Match Timestamp and drop picoseconds, femtoseconds, attoseconds
# The new resolution will just be nano
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GH ref pointing back here?

if out_bestunit in {NPY_DATETIMEUNIT.NPY_FR_ps,
NPY_DATETIMEUNIT.NPY_FR_fs,
NPY_DATETIMEUNIT.NPY_FR_as}:
out_bestunit = NPY_DATETIMEUNIT.NPY_FR_ns
reso = {
NPY_DATETIMEUNIT.NPY_FR_Y: "year",
NPY_DATETIMEUNIT.NPY_FR_M: "month",
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5 changes: 5 additions & 0 deletions pandas/tests/scalar/period/test_period.py
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Expand Up @@ -545,6 +545,11 @@ def test_period_cons_combined(self):
(".000000999", 999),
(".123456789", 789),
(".999999999", 999),
(".999999000", 0),
# Test femtoseconds, attoseconds, picoseconds are dropped like Timestamp
(".999999001123", 1),
(".999999001123456", 1),
(".999999001123456789", 1),
],
)
def test_period_constructor_nanosecond(self, day, hour, sec_float, expected):
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