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ENH: support nanoseconds in Period constructor #38175

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Merged
merged 13 commits into from
Dec 2, 2020
Merged

ENH: support nanoseconds in Period constructor #38175

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91a7c7e
BUG #34621 added nanosecond support to class Period
Jun 11, 2020
73a6eab
BUG #34621 added tests
Jun 12, 2020
ea9f69c
BUG #34621 added tests (black pandas passed)
Jun 12, 2020
ab5640f
#34131 fix one test failure
Jun 13, 2020
95d740e
#34621 review taken into account
Jun 15, 2020
abb0936
#34621 review taken into account, and suppress a bad copy/paste on li…
Jun 15, 2020
8a559cb
#34621 Added nanosecond support to Period constructor
Jun 16, 2020
2b2f1d0
merge with master
arw2019 Nov 30, 2020
63e72d8
rewrite test
arw2019 Nov 30, 2020
e511df3
merge master
arw2019 Nov 30, 2020
55cf0ac
whatsnew
arw2019 Dec 2, 2020
737ce75
merge conflict
arw2019 Dec 2, 2020
9a41f1a
Merge branch 'master' of https://github.com/pandas-dev/pandas into GH…
arw2019 Dec 2, 2020
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11 changes: 10 additions & 1 deletion pandas/_libs/tslibs/period.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -2345,6 +2345,7 @@ class Period(_Period):

if freq is not None:
freq = cls._maybe_convert_freq(freq)
nanosecond = 0

if ordinal is not None and value is not None:
raise ValueError("Only value or ordinal but not both should be "
Expand Down Expand Up @@ -2394,6 +2395,14 @@ class Period(_Period):
value = str(value)
value = value.upper()
dt, reso = parse_time_string(value, freq)
try:
ts = Timestamp(value)
Comment on lines 2397 to +2399
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Aren't we effectively doing the parsing twice, this way? (once in parse_time_string, once in Timestamp) Any way to avoid this?

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Yes - @jreback suggested integrating this a bit more into parse_time_string

I opened #38312 to track resolution (I'll have a go at it if no one else does)

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Thanks!

except ValueError:
nanosecond = 0
else:
nanosecond = ts.nanosecond
if nanosecond != 0:
reso = 'nanosecond'
if dt is NaT:
ordinal = NPY_NAT

Expand Down Expand Up @@ -2425,7 +2434,7 @@ class Period(_Period):
base = freq_to_dtype_code(freq)
ordinal = period_ordinal(dt.year, dt.month, dt.day,
dt.hour, dt.minute, dt.second,
dt.microsecond, 0, base)
dt.microsecond, 1000*nanosecond, base)

return cls._from_ordinal(ordinal, freq)

Expand Down
16 changes: 16 additions & 0 deletions pandas/tests/scalar/period/test_period.py
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Expand Up @@ -487,6 +487,22 @@ def test_period_cons_combined(self):
with pytest.raises(ValueError, match=msg):
Period("2011-01", freq="1D1W")

@pytest.mark.parametrize("day", ["1970/01/01 ", "2020-12-31 ", "1981/09/13 "])
@pytest.mark.parametrize("hour", ["00:00:00", "00:00:01", "23:59:59", "12:00:59"])
@pytest.mark.parametrize(
"sec_float, expected",
[
(".000000001", 1),
(".000000999", 999),
(".123456789", 789),
(".999999999", 999),
],
)
def test_period_constructor_nanosecond(self, day, hour, sec_float, expected):
# GH 34621

assert Period(day + hour + sec_float).start_time.nanosecond == expected

@pytest.mark.parametrize("hour", range(24))
def test_period_large_ordinal(self, hour):
# Issue #36430
Expand Down