Skip to content

DEPR: Undeprecate period - integer addition #24352

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Dec 23, 2018
Merged

DEPR: Undeprecate period - integer addition #24352

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
76d8655
DEPR: Undeprecate period - integer addition
TomAugspurger Dec 19, 2018
d2351bf
one more
TomAugspurger Dec 19, 2018
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
24 changes: 6 additions & 18 deletions doc/source/whatsnew/v0.24.0.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1149,25 +1149,19 @@ Deprecations

.. _whatsnew_0240.deprecations.datetimelike_int_ops:

Integer Addition/Subtraction with Datetime-like Classes Is Deprecated
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In the past, users could add or subtract integers or integer-dtypes arrays
from :class:`Period`, :class:`PeriodIndex`, and in some cases
:class:`Timestamp`, :class:`DatetimeIndex` and :class:`TimedeltaIndex`.
Integer Addition/Subtraction with Datetimes and Timedeltas is Deprecated
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the past, users could—in some cases—add or subtract integers or integer-dtype
arrays from :class:`Timestamp`, :class:`DatetimeIndex` and :class:`TimedeltaIndex`.

This usage is now deprecated. Instead add or subtract integer multiples of
the object's ``freq`` attribute. The result of subtraction of :class:`Period`
objects will be agnostic of the multiplier of the objects' ``freq`` attribute
(:issue:`21939`, :issue:`23878`).
the object's ``freq`` attribute (:issue:`21939`, :issue:`23878`).

*Previous Behavior*:

.. code-block:: ipython

In [3]: per = pd.Period('2016Q1')
In [4]: per + 3
Out[4]: Period('2016Q4', 'Q-DEC')

In [5]: ts = pd.Timestamp('1994-05-06 12:15:16', freq=pd.offsets.Hour())
In [6]: ts + 2
Out[6]: Timestamp('1994-05-06 14:15:16', freq='H')
Expand All @@ -1185,12 +1179,6 @@ objects will be agnostic of the multiplier of the objects' ``freq`` attribute
.. ipython:: python
:okwarning:

per = pd.Period('2016Q1')
per + 3

per = pd.Period('2016Q1')
per + 3 * per.freq

ts = pd.Timestamp('1994-05-06 12:15:16', freq=pd.offsets.Hour())
ts + 2 * ts.freq

Expand Down
6 changes: 1 addition & 5 deletions pandas/_libs/tslibs/period.pyx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ cdef extern from "src/datetime/np_datetime.h":
cimport util
from util cimport is_period_object, is_string_object

from timestamps import Timestamp, maybe_integer_op_deprecated
from timestamps import Timestamp
from timezones cimport is_utc, is_tzlocal, get_dst_info
from timedeltas import Timedelta
from timedeltas cimport delta_to_nanoseconds
Expand Down Expand Up @@ -1655,8 +1655,6 @@ cdef class _Period(object):
elif other is NaT:
return NaT
elif util.is_integer_object(other):
maybe_integer_op_deprecated(self)

ordinal = self.ordinal + other * self.freq.n
return Period(ordinal=ordinal, freq=self.freq)
elif (PyDateTime_Check(other) or
Expand All @@ -1683,8 +1681,6 @@ cdef class _Period(object):
neg_other = -other
return self + neg_other
elif util.is_integer_object(other):
maybe_integer_op_deprecated(self)

ordinal = self.ordinal - other * self.freq.n
return Period(ordinal=ordinal, freq=self.freq)
elif is_period_object(other):
Expand Down
12 changes: 8 additions & 4 deletions pandas/core/arrays/datetimelike.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -905,7 +905,8 @@ def __add__(self, other):
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
maybe_integer_op_deprecated(self)
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._time_shift(other)

# array-like others
Expand All @@ -919,7 +920,8 @@ def __add__(self, other):
# DatetimeIndex, ndarray[datetime64]
return self._add_datetime_arraylike(other)
elif is_integer_dtype(other):
maybe_integer_op_deprecated(self)
if not is_period_dtype(self):
Copy link
Contributor Author

@TomAugspurger TomAugspurger Dec 19, 2018 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

These repeated if checks could maybe be moved into the maybe_integer_op_deprecated. @jbrockmendel is there a recommended Cython equivalent for is_period_dtype?

maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.add)
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
Expand Down Expand Up @@ -966,7 +968,8 @@ def __sub__(self, other):
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
maybe_integer_op_deprecated(self)
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._time_shift(-other)

elif isinstance(other, Period):
Expand All @@ -986,7 +989,8 @@ def __sub__(self, other):
# PeriodIndex
result = self._sub_period_array(other)
elif is_integer_dtype(other):
maybe_integer_op_deprecated(self)
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.sub)
elif isinstance(other, ABCIndexClass):
raise TypeError("cannot subtract {cls} and {typ}"
Expand Down
116 changes: 49 additions & 67 deletions pandas/tests/arithmetic/test_period.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -557,14 +557,10 @@ def test_pi_sub_offset_array(self, box):
def test_pi_add_iadd_int(self, one):
# Variants of `one` for #19012
rng = pd.period_range('2000-01-01 09:00', freq='H', periods=10)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
result = rng + one
result = rng + one
expected = pd.period_range('2000-01-01 10:00', freq='H', periods=10)
tm.assert_index_equal(result, expected)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
rng += one
rng += one
tm.assert_index_equal(rng, expected)

def test_pi_sub_isub_int(self, one):
Expand All @@ -573,24 +569,18 @@ def test_pi_sub_isub_int(self, one):
the integer 1, e.g. int, long, np.int64, np.uint8, ...
"""
rng = pd.period_range('2000-01-01 09:00', freq='H', periods=10)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
result = rng - one
result = rng - one
expected = pd.period_range('2000-01-01 08:00', freq='H', periods=10)
tm.assert_index_equal(result, expected)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
rng -= one
rng -= one
tm.assert_index_equal(rng, expected)

@pytest.mark.parametrize('five', [5, np.array(5, dtype=np.int64)])
def test_pi_sub_intlike(self, five):
rng = period_range('2007-01', periods=50)

with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
result = rng - five
exp = rng + (-five)
result = rng - five
exp = rng + (-five)
tm.assert_index_equal(result, exp)

def test_pi_sub_isub_offset(self):
Expand Down Expand Up @@ -655,9 +645,8 @@ def test_pi_add_intarray(self, int_holder, op):
# GH#19959
pi = pd.PeriodIndex([pd.Period('2015Q1'), pd.Period('NaT')])
other = int_holder([4, -1])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
result = op(pi, other)

result = op(pi, other)
expected = pd.PeriodIndex([pd.Period('2016Q1'), pd.Period('NaT')])
tm.assert_index_equal(result, expected)

Expand All @@ -666,16 +655,13 @@ def test_pi_sub_intarray(self, int_holder):
# GH#19959
pi = pd.PeriodIndex([pd.Period('2015Q1'), pd.Period('NaT')])
other = int_holder([4, -1])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
result = pi - other

result = pi - other
expected = pd.PeriodIndex([pd.Period('2014Q1'), pd.Period('NaT')])
tm.assert_index_equal(result, expected)

with pytest.raises(TypeError):
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
other - pi
other - pi

# ---------------------------------------------------------------
# Timedelta-like (timedelta, timedelta64, Timedelta, Tick)
Expand Down Expand Up @@ -937,12 +923,11 @@ def test_pi_ops(self):

expected = PeriodIndex(['2011-03', '2011-04', '2011-05', '2011-06'],
freq='M', name='idx')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
self._check(idx, lambda x: x + 2, expected)
self._check(idx, lambda x: 2 + x, expected)

self._check(idx + 2, lambda x: x - 2, idx)
self._check(idx, lambda x: x + 2, expected)
self._check(idx, lambda x: 2 + x, expected)

self._check(idx + 2, lambda x: x - 2, idx)

result = idx - Period('2011-01', freq='M')
off = idx.freq
Expand Down Expand Up @@ -987,53 +972,50 @@ def test_pi_ops_nat(self):
freq='M', name='idx')
expected = PeriodIndex(['2011-03', '2011-04', 'NaT', '2011-06'],
freq='M', name='idx')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
self._check(idx, lambda x: x + 2, expected)
self._check(idx, lambda x: 2 + x, expected)
self._check(idx, lambda x: np.add(x, 2), expected)

self._check(idx + 2, lambda x: x - 2, idx)
self._check(idx + 2, lambda x: np.subtract(x, 2), idx)
self._check(idx, lambda x: x + 2, expected)
self._check(idx, lambda x: 2 + x, expected)
self._check(idx, lambda x: np.add(x, 2), expected)

self._check(idx + 2, lambda x: x - 2, idx)
self._check(idx + 2, lambda x: np.subtract(x, 2), idx)

# freq with mult
idx = PeriodIndex(['2011-01', '2011-02', 'NaT', '2011-04'],
freq='2M', name='idx')
expected = PeriodIndex(['2011-07', '2011-08', 'NaT', '2011-10'],
freq='2M', name='idx')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
self._check(idx, lambda x: x + 3, expected)
self._check(idx, lambda x: 3 + x, expected)
self._check(idx, lambda x: np.add(x, 3), expected)

self._check(idx + 3, lambda x: x - 3, idx)
self._check(idx + 3, lambda x: np.subtract(x, 3), idx)
self._check(idx, lambda x: x + 3, expected)
self._check(idx, lambda x: 3 + x, expected)
self._check(idx, lambda x: np.add(x, 3), expected)

self._check(idx + 3, lambda x: x - 3, idx)
self._check(idx + 3, lambda x: np.subtract(x, 3), idx)

def test_pi_ops_array_int(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False,
clear=[pd.core.arrays.datetimelike]):
idx = PeriodIndex(['2011-01', '2011-02', 'NaT', '2011-04'],
freq='M', name='idx')
f = lambda x: x + np.array([1, 2, 3, 4])
exp = PeriodIndex(['2011-02', '2011-04', 'NaT', '2011-08'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: np.add(x, np.array([4, -1, 1, 2]))
exp = PeriodIndex(['2011-05', '2011-01', 'NaT', '2011-06'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: x - np.array([1, 2, 3, 4])
exp = PeriodIndex(['2010-12', '2010-12', 'NaT', '2010-12'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: np.subtract(x, np.array([3, 2, 3, -2]))
exp = PeriodIndex(['2010-10', '2010-12', 'NaT', '2011-06'],
freq='M', name='idx')
self._check(idx, f, exp)

idx = PeriodIndex(['2011-01', '2011-02', 'NaT', '2011-04'],
freq='M', name='idx')
f = lambda x: x + np.array([1, 2, 3, 4])
exp = PeriodIndex(['2011-02', '2011-04', 'NaT', '2011-08'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: np.add(x, np.array([4, -1, 1, 2]))
exp = PeriodIndex(['2011-05', '2011-01', 'NaT', '2011-06'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: x - np.array([1, 2, 3, 4])
exp = PeriodIndex(['2010-12', '2010-12', 'NaT', '2010-12'],
freq='M', name='idx')
self._check(idx, f, exp)

f = lambda x: np.subtract(x, np.array([3, 2, 3, -2]))
exp = PeriodIndex(['2010-10', '2010-12', 'NaT', '2011-06'],
freq='M', name='idx')
self._check(idx, f, exp)

def test_pi_ops_offset(self):
idx = PeriodIndex(['2011-01-01', '2011-02-01', '2011-03-01',
Expand Down
7 changes: 3 additions & 4 deletions pandas/tests/indexes/period/test_period.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -339,10 +339,9 @@ def test_is_(self):
assert not index.is_(index[:])
assert not index.is_(index.asfreq('M'))
assert not index.is_(index.asfreq('A'))
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
# GH#22535
assert not index.is_(index - 2)
assert not index.is_(index - 0)

assert not index.is_(index - 2)
assert not index.is_(index - 0)

def test_contains(self):
rng = period_range('2007-01', freq='M', periods=10)
Expand Down
9 changes: 3 additions & 6 deletions pandas/tests/scalar/period/test_asfreq.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@
from pandas.errors import OutOfBoundsDatetime

from pandas import Period, offsets
from pandas.util import testing as tm


class TestFreqConversion(object):
Expand All @@ -16,17 +15,15 @@ def test_asfreq_near_zero(self, freq):
per = Period('0001-01-01', freq=freq)
tup1 = (per.year, per.hour, per.day)

with tm.assert_produces_warning(FutureWarning):
prev = per - 1
prev = per - 1
assert prev.ordinal == per.ordinal - 1
tup2 = (prev.year, prev.month, prev.day)
assert tup2 < tup1

def test_asfreq_near_zero_weekly(self):
# GH#19834
with tm.assert_produces_warning(FutureWarning):
per1 = Period('0001-01-01', 'D') + 6
per2 = Period('0001-01-01', 'D') - 6
per1 = Period('0001-01-01', 'D') + 6
per2 = Period('0001-01-01', 'D') - 6
week1 = per1.asfreq('W')
week2 = per2.asfreq('W')
assert week1 != week2
Expand Down
Loading