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test_period.py
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# Arithmetic tests for DataFrame/Series/Index/Array classes that should
# behave identically.
# Specifically for Period dtype
import operator
import numpy as np
import pytest
from pandas._libs.tslibs import (
IncompatibleFrequency,
Period,
Timestamp,
to_offset,
)
from pandas.errors import PerformanceWarning
import pandas as pd
from pandas import (
PeriodIndex,
Series,
Timedelta,
TimedeltaIndex,
period_range,
)
import pandas._testing as tm
from pandas.core import ops
from pandas.core.arrays import TimedeltaArray
from pandas.tests.arithmetic.common import (
assert_invalid_addsub_type,
assert_invalid_comparison,
get_upcast_box,
)
# ------------------------------------------------------------------
# Comparisons
class TestPeriodArrayLikeComparisons:
# Comparison tests for PeriodDtype vectors fully parametrized over
# DataFrame/Series/PeriodIndex/PeriodArray. Ideally all comparison
# tests will eventually end up here.
@pytest.mark.parametrize("other", ["2017", Period("2017", freq="D")])
def test_eq_scalar(self, other, box_with_array):
idx = PeriodIndex(["2017", "2017", "2018"], freq="D")
idx = tm.box_expected(idx, box_with_array)
xbox = get_upcast_box(idx, other, True)
expected = np.array([True, True, False])
expected = tm.box_expected(expected, xbox)
result = idx == other
tm.assert_equal(result, expected)
def test_compare_zerodim(self, box_with_array):
# GH#26689 make sure we unbox zero-dimensional arrays
pi = period_range("2000", periods=4)
other = np.array(pi.to_numpy()[0])
pi = tm.box_expected(pi, box_with_array)
xbox = get_upcast_box(pi, other, True)
result = pi <= other
expected = np.array([True, False, False, False])
expected = tm.box_expected(expected, xbox)
tm.assert_equal(result, expected)
@pytest.mark.parametrize(
"scalar",
[
"foo",
Timestamp("2021-01-01"),
Timedelta(days=4),
9,
9.5,
2000, # specifically don't consider 2000 to match Period("2000", "D")
False,
None,
],
)
def test_compare_invalid_scalar(self, box_with_array, scalar):
# GH#28980
# comparison with scalar that cannot be interpreted as a Period
pi = period_range("2000", periods=4)
parr = tm.box_expected(pi, box_with_array)
assert_invalid_comparison(parr, scalar, box_with_array)
@pytest.mark.parametrize(
"other",
[
pd.date_range("2000", periods=4).array,
pd.timedelta_range("1D", periods=4).array,
np.arange(4),
np.arange(4).astype(np.float64),
list(range(4)),
# match Period semantics by not treating integers as Periods
[2000, 2001, 2002, 2003],
np.arange(2000, 2004),
np.arange(2000, 2004).astype(object),
pd.Index([2000, 2001, 2002, 2003]),
],
)
def test_compare_invalid_listlike(self, box_with_array, other):
pi = period_range("2000", periods=4)
parr = tm.box_expected(pi, box_with_array)
assert_invalid_comparison(parr, other, box_with_array)
@pytest.mark.parametrize("other_box", [list, np.array, lambda x: x.astype(object)])
def test_compare_object_dtype(self, box_with_array, other_box):
pi = period_range("2000", periods=5)
parr = tm.box_expected(pi, box_with_array)
other = other_box(pi)
xbox = get_upcast_box(parr, other, True)
expected = np.array([True, True, True, True, True])
expected = tm.box_expected(expected, xbox)
result = parr == other
tm.assert_equal(result, expected)
result = parr <= other
tm.assert_equal(result, expected)
result = parr >= other
tm.assert_equal(result, expected)
result = parr != other
tm.assert_equal(result, ~expected)
result = parr < other
tm.assert_equal(result, ~expected)
result = parr > other
tm.assert_equal(result, ~expected)
other = other_box(pi[::-1])
expected = np.array([False, False, True, False, False])
expected = tm.box_expected(expected, xbox)
result = parr == other
tm.assert_equal(result, expected)
expected = np.array([True, True, True, False, False])
expected = tm.box_expected(expected, xbox)
result = parr <= other
tm.assert_equal(result, expected)
expected = np.array([False, False, True, True, True])
expected = tm.box_expected(expected, xbox)
result = parr >= other
tm.assert_equal(result, expected)
expected = np.array([True, True, False, True, True])
expected = tm.box_expected(expected, xbox)
result = parr != other
tm.assert_equal(result, expected)
expected = np.array([True, True, False, False, False])
expected = tm.box_expected(expected, xbox)
result = parr < other
tm.assert_equal(result, expected)
expected = np.array([False, False, False, True, True])
expected = tm.box_expected(expected, xbox)
result = parr > other
tm.assert_equal(result, expected)
class TestPeriodIndexComparisons:
# TODO: parameterize over boxes
def test_pi_cmp_period(self):
idx = period_range("2007-01", periods=20, freq="M")
per = idx[10]
result = idx < per
exp = idx.values < idx.values[10]
tm.assert_numpy_array_equal(result, exp)
# Tests Period.__richcmp__ against ndarray[object, ndim=2]
result = idx.values.reshape(10, 2) < per
tm.assert_numpy_array_equal(result, exp.reshape(10, 2))
# Tests Period.__richcmp__ against ndarray[object, ndim=0]
result = idx < np.array(per)
tm.assert_numpy_array_equal(result, exp)
# TODO: moved from test_datetime64; de-duplicate with version below
def test_parr_cmp_period_scalar2(self, box_with_array):
pi = period_range("2000-01-01", periods=10, freq="D")
val = pi[3]
expected = [x > val for x in pi]
ser = tm.box_expected(pi, box_with_array)
xbox = get_upcast_box(ser, val, True)
expected = tm.box_expected(expected, xbox)
result = ser > val
tm.assert_equal(result, expected)
val = pi[5]
result = ser > val
expected = [x > val for x in pi]
expected = tm.box_expected(expected, xbox)
tm.assert_equal(result, expected)
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_parr_cmp_period_scalar(self, freq, box_with_array):
# GH#13200
base = PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq=freq)
base = tm.box_expected(base, box_with_array)
per = Period("2011-02", freq=freq)
xbox = get_upcast_box(base, per, True)
exp = np.array([False, True, False, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base == per, exp)
tm.assert_equal(per == base, exp)
exp = np.array([True, False, True, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base != per, exp)
tm.assert_equal(per != base, exp)
exp = np.array([False, False, True, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base > per, exp)
tm.assert_equal(per < base, exp)
exp = np.array([True, False, False, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base < per, exp)
tm.assert_equal(per > base, exp)
exp = np.array([False, True, True, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base >= per, exp)
tm.assert_equal(per <= base, exp)
exp = np.array([True, True, False, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base <= per, exp)
tm.assert_equal(per >= base, exp)
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_parr_cmp_pi(self, freq, box_with_array):
# GH#13200
base = PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq=freq)
base = tm.box_expected(base, box_with_array)
# TODO: could also box idx?
idx = PeriodIndex(["2011-02", "2011-01", "2011-03", "2011-05"], freq=freq)
xbox = get_upcast_box(base, idx, True)
exp = np.array([False, False, True, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base == idx, exp)
exp = np.array([True, True, False, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base != idx, exp)
exp = np.array([False, True, False, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base > idx, exp)
exp = np.array([True, False, False, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base < idx, exp)
exp = np.array([False, True, True, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base >= idx, exp)
exp = np.array([True, False, True, True])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base <= idx, exp)
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_parr_cmp_pi_mismatched_freq(self, freq, box_with_array):
# GH#13200
# different base freq
base = PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq=freq)
base = tm.box_expected(base, box_with_array)
msg = rf"Invalid comparison between dtype=period\[{freq}\] and Period"
with pytest.raises(TypeError, match=msg):
base <= Period("2011", freq="A")
with pytest.raises(TypeError, match=msg):
Period("2011", freq="A") >= base
# TODO: Could parametrize over boxes for idx?
idx = PeriodIndex(["2011", "2012", "2013", "2014"], freq="A")
rev_msg = r"Invalid comparison between dtype=period\[A-DEC\] and PeriodArray"
idx_msg = rev_msg if box_with_array in [tm.to_array, pd.array] else msg
with pytest.raises(TypeError, match=idx_msg):
base <= idx
# Different frequency
msg = rf"Invalid comparison between dtype=period\[{freq}\] and Period"
with pytest.raises(TypeError, match=msg):
base <= Period("2011", freq="4M")
with pytest.raises(TypeError, match=msg):
Period("2011", freq="4M") >= base
idx = PeriodIndex(["2011", "2012", "2013", "2014"], freq="4M")
rev_msg = r"Invalid comparison between dtype=period\[4M\] and PeriodArray"
idx_msg = rev_msg if box_with_array in [tm.to_array, pd.array] else msg
with pytest.raises(TypeError, match=idx_msg):
base <= idx
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_pi_cmp_nat(self, freq):
idx1 = PeriodIndex(["2011-01", "2011-02", "NaT", "2011-05"], freq=freq)
per = idx1[1]
result = idx1 > per
exp = np.array([False, False, False, True])
tm.assert_numpy_array_equal(result, exp)
result = per < idx1
tm.assert_numpy_array_equal(result, exp)
result = idx1 == pd.NaT
exp = np.array([False, False, False, False])
tm.assert_numpy_array_equal(result, exp)
result = pd.NaT == idx1
tm.assert_numpy_array_equal(result, exp)
result = idx1 != pd.NaT
exp = np.array([True, True, True, True])
tm.assert_numpy_array_equal(result, exp)
result = pd.NaT != idx1
tm.assert_numpy_array_equal(result, exp)
idx2 = PeriodIndex(["2011-02", "2011-01", "2011-04", "NaT"], freq=freq)
result = idx1 < idx2
exp = np.array([True, False, False, False])
tm.assert_numpy_array_equal(result, exp)
result = idx1 == idx2
exp = np.array([False, False, False, False])
tm.assert_numpy_array_equal(result, exp)
result = idx1 != idx2
exp = np.array([True, True, True, True])
tm.assert_numpy_array_equal(result, exp)
result = idx1 == idx1
exp = np.array([True, True, False, True])
tm.assert_numpy_array_equal(result, exp)
result = idx1 != idx1
exp = np.array([False, False, True, False])
tm.assert_numpy_array_equal(result, exp)
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_pi_cmp_nat_mismatched_freq_raises(self, freq):
idx1 = PeriodIndex(["2011-01", "2011-02", "NaT", "2011-05"], freq=freq)
diff = PeriodIndex(["2011-02", "2011-01", "2011-04", "NaT"], freq="4M")
msg = rf"Invalid comparison between dtype=period\[{freq}\] and PeriodArray"
with pytest.raises(TypeError, match=msg):
idx1 > diff
result = idx1 == diff
expected = np.array([False, False, False, False], dtype=bool)
tm.assert_numpy_array_equal(result, expected)
# TODO: De-duplicate with test_pi_cmp_nat
@pytest.mark.parametrize("dtype", [object, None])
def test_comp_nat(self, dtype):
left = PeriodIndex([Period("2011-01-01"), pd.NaT, Period("2011-01-03")])
right = PeriodIndex([pd.NaT, pd.NaT, Period("2011-01-03")])
if dtype is not None:
left = left.astype(dtype)
right = right.astype(dtype)
result = left == right
expected = np.array([False, False, True])
tm.assert_numpy_array_equal(result, expected)
result = left != right
expected = np.array([True, True, False])
tm.assert_numpy_array_equal(result, expected)
expected = np.array([False, False, False])
tm.assert_numpy_array_equal(left == pd.NaT, expected)
tm.assert_numpy_array_equal(pd.NaT == right, expected)
expected = np.array([True, True, True])
tm.assert_numpy_array_equal(left != pd.NaT, expected)
tm.assert_numpy_array_equal(pd.NaT != left, expected)
expected = np.array([False, False, False])
tm.assert_numpy_array_equal(left < pd.NaT, expected)
tm.assert_numpy_array_equal(pd.NaT > left, expected)
class TestPeriodSeriesComparisons:
def test_cmp_series_period_series_mixed_freq(self):
# GH#13200
base = Series(
[
Period("2011", freq="A"),
Period("2011-02", freq="M"),
Period("2013", freq="A"),
Period("2011-04", freq="M"),
]
)
ser = Series(
[
Period("2012", freq="A"),
Period("2011-01", freq="M"),
Period("2013", freq="A"),
Period("2011-05", freq="M"),
]
)
exp = Series([False, False, True, False])
tm.assert_series_equal(base == ser, exp)
exp = Series([True, True, False, True])
tm.assert_series_equal(base != ser, exp)
exp = Series([False, True, False, False])
tm.assert_series_equal(base > ser, exp)
exp = Series([True, False, False, True])
tm.assert_series_equal(base < ser, exp)
exp = Series([False, True, True, False])
tm.assert_series_equal(base >= ser, exp)
exp = Series([True, False, True, True])
tm.assert_series_equal(base <= ser, exp)
class TestPeriodIndexSeriesComparisonConsistency:
"""Test PeriodIndex and Period Series Ops consistency"""
# TODO: needs parametrization+de-duplication
def _check(self, values, func, expected):
# Test PeriodIndex and Period Series Ops consistency
idx = PeriodIndex(values)
result = func(idx)
# check that we don't pass an unwanted type to tm.assert_equal
assert isinstance(expected, (pd.Index, np.ndarray))
tm.assert_equal(result, expected)
s = Series(values)
result = func(s)
exp = Series(expected, name=values.name)
tm.assert_series_equal(result, exp)
def test_pi_comp_period(self):
idx = PeriodIndex(
["2011-01", "2011-02", "2011-03", "2011-04"], freq="M", name="idx"
)
per = idx[2]
f = lambda x: x == per
exp = np.array([False, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: per == x
self._check(idx, f, exp)
f = lambda x: x != per
exp = np.array([True, True, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: per != x
self._check(idx, f, exp)
f = lambda x: per >= x
exp = np.array([True, True, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: x > per
exp = np.array([False, False, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: per >= x
exp = np.array([True, True, True, False], dtype=np.bool_)
self._check(idx, f, exp)
def test_pi_comp_period_nat(self):
idx = PeriodIndex(
["2011-01", "NaT", "2011-03", "2011-04"], freq="M", name="idx"
)
per = idx[2]
f = lambda x: x == per
exp = np.array([False, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: per == x
self._check(idx, f, exp)
f = lambda x: x == pd.NaT
exp = np.array([False, False, False, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.NaT == x
self._check(idx, f, exp)
f = lambda x: x != per
exp = np.array([True, True, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: per != x
self._check(idx, f, exp)
f = lambda x: x != pd.NaT
exp = np.array([True, True, True, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.NaT != x
self._check(idx, f, exp)
f = lambda x: per >= x
exp = np.array([True, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: x < per
exp = np.array([True, False, False, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: x > pd.NaT
exp = np.array([False, False, False, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.NaT >= x
exp = np.array([False, False, False, False], dtype=np.bool_)
self._check(idx, f, exp)
# ------------------------------------------------------------------
# Arithmetic
class TestPeriodFrameArithmetic:
def test_ops_frame_period(self):
# GH#13043
df = pd.DataFrame(
{
"A": [Period("2015-01", freq="M"), Period("2015-02", freq="M")],
"B": [Period("2014-01", freq="M"), Period("2014-02", freq="M")],
}
)
assert df["A"].dtype == "Period[M]"
assert df["B"].dtype == "Period[M]"
p = Period("2015-03", freq="M")
off = p.freq
# dtype will be object because of original dtype
exp = pd.DataFrame(
{
"A": np.array([2 * off, 1 * off], dtype=object),
"B": np.array([14 * off, 13 * off], dtype=object),
}
)
tm.assert_frame_equal(p - df, exp)
tm.assert_frame_equal(df - p, -1 * exp)
df2 = pd.DataFrame(
{
"A": [Period("2015-05", freq="M"), Period("2015-06", freq="M")],
"B": [Period("2015-05", freq="M"), Period("2015-06", freq="M")],
}
)
assert df2["A"].dtype == "Period[M]"
assert df2["B"].dtype == "Period[M]"
exp = pd.DataFrame(
{
"A": np.array([4 * off, 4 * off], dtype=object),
"B": np.array([16 * off, 16 * off], dtype=object),
}
)
tm.assert_frame_equal(df2 - df, exp)
tm.assert_frame_equal(df - df2, -1 * exp)
class TestPeriodIndexArithmetic:
# ---------------------------------------------------------------
# __add__/__sub__ with PeriodIndex
# PeriodIndex + other is defined for integers and timedelta-like others
# PeriodIndex - other is defined for integers, timedelta-like others,
# and PeriodIndex (with matching freq)
def test_parr_add_iadd_parr_raises(self, box_with_array):
rng = period_range("1/1/2000", freq="D", periods=5)
other = period_range("1/6/2000", freq="D", periods=5)
# TODO: parametrize over boxes for other?
rng = tm.box_expected(rng, box_with_array)
# An earlier implementation of PeriodIndex addition performed
# a set operation (union). This has since been changed to
# raise a TypeError. See GH#14164 and GH#13077 for historical
# reference.
msg = r"unsupported operand type\(s\) for \+: .* and .*"
with pytest.raises(TypeError, match=msg):
rng + other
with pytest.raises(TypeError, match=msg):
rng += other
def test_pi_sub_isub_pi(self):
# GH#20049
# For historical reference see GH#14164, GH#13077.
# PeriodIndex subtraction originally performed set difference,
# then changed to raise TypeError before being implemented in GH#20049
rng = period_range("1/1/2000", freq="D", periods=5)
other = period_range("1/6/2000", freq="D", periods=5)
off = rng.freq
expected = pd.Index([-5 * off] * 5)
result = rng - other
tm.assert_index_equal(result, expected)
rng -= other
tm.assert_index_equal(rng, expected)
def test_pi_sub_pi_with_nat(self):
rng = period_range("1/1/2000", freq="D", periods=5)
other = rng[1:].insert(0, pd.NaT)
assert other[1:].equals(rng[1:])
result = rng - other
off = rng.freq
expected = pd.Index([pd.NaT, 0 * off, 0 * off, 0 * off, 0 * off])
tm.assert_index_equal(result, expected)
def test_parr_sub_pi_mismatched_freq(self, box_with_array, box_with_array2):
rng = period_range("1/1/2000", freq="D", periods=5)
other = period_range("1/6/2000", freq="H", periods=5)
rng = tm.box_expected(rng, box_with_array)
other = tm.box_expected(other, box_with_array2)
msg = r"Input has different freq=[HD] from PeriodArray\(freq=[DH]\)"
with pytest.raises(IncompatibleFrequency, match=msg):
rng - other
@pytest.mark.parametrize("n", [1, 2, 3, 4])
def test_sub_n_gt_1_ticks(self, tick_classes, n):
# GH 23878
p1_d = "19910905"
p2_d = "19920406"
p1 = PeriodIndex([p1_d], freq=tick_classes(n))
p2 = PeriodIndex([p2_d], freq=tick_classes(n))
expected = PeriodIndex([p2_d], freq=p2.freq.base) - PeriodIndex(
[p1_d], freq=p1.freq.base
)
tm.assert_index_equal((p2 - p1), expected)
@pytest.mark.parametrize("n", [1, 2, 3, 4])
@pytest.mark.parametrize(
"offset, kwd_name",
[
(pd.offsets.YearEnd, "month"),
(pd.offsets.QuarterEnd, "startingMonth"),
(pd.offsets.MonthEnd, None),
(pd.offsets.Week, "weekday"),
],
)
def test_sub_n_gt_1_offsets(self, offset, kwd_name, n):
# GH 23878
kwds = {kwd_name: 3} if kwd_name is not None else {}
p1_d = "19910905"
p2_d = "19920406"
freq = offset(n, normalize=False, **kwds)
p1 = PeriodIndex([p1_d], freq=freq)
p2 = PeriodIndex([p2_d], freq=freq)
result = p2 - p1
expected = PeriodIndex([p2_d], freq=freq.base) - PeriodIndex(
[p1_d], freq=freq.base
)
tm.assert_index_equal(result, expected)
# -------------------------------------------------------------
# Invalid Operations
@pytest.mark.parametrize(
"other",
[
# datetime scalars
Timestamp("2016-01-01"),
Timestamp("2016-01-01").to_pydatetime(),
Timestamp("2016-01-01").to_datetime64(),
# datetime-like arrays
pd.date_range("2016-01-01", periods=3, freq="H"),
pd.date_range("2016-01-01", periods=3, tz="Europe/Brussels"),
pd.date_range("2016-01-01", periods=3, freq="S")._data,
pd.date_range("2016-01-01", periods=3, tz="Asia/Tokyo")._data,
# Miscellaneous invalid types
3.14,
np.array([2.0, 3.0, 4.0]),
],
)
def test_parr_add_sub_invalid(self, other, box_with_array):
# GH#23215
rng = period_range("1/1/2000", freq="D", periods=3)
rng = tm.box_expected(rng, box_with_array)
msg = "|".join(
[
r"(:?cannot add PeriodArray and .*)",
r"(:?cannot subtract .* from (:?a\s)?.*)",
r"(:?unsupported operand type\(s\) for \+: .* and .*)",
r"unsupported operand type\(s\) for [+-]: .* and .*",
]
)
assert_invalid_addsub_type(rng, other, msg)
with pytest.raises(TypeError, match=msg):
rng + other
with pytest.raises(TypeError, match=msg):
other + rng
with pytest.raises(TypeError, match=msg):
rng - other
with pytest.raises(TypeError, match=msg):
other - rng
# -----------------------------------------------------------------
# __add__/__sub__ with ndarray[datetime64] and ndarray[timedelta64]
def test_pi_add_sub_td64_array_non_tick_raises(self):
rng = period_range("1/1/2000", freq="Q", periods=3)
tdi = TimedeltaIndex(["-1 Day", "-1 Day", "-1 Day"])
tdarr = tdi.values
msg = r"Cannot add or subtract timedelta64\[ns\] dtype from period\[Q-DEC\]"
with pytest.raises(TypeError, match=msg):
rng + tdarr
with pytest.raises(TypeError, match=msg):
tdarr + rng
with pytest.raises(TypeError, match=msg):
rng - tdarr
msg = r"cannot subtract PeriodArray from TimedeltaArray"
with pytest.raises(TypeError, match=msg):
tdarr - rng
def test_pi_add_sub_td64_array_tick(self):
# PeriodIndex + Timedelta-like is allowed only with
# tick-like frequencies
rng = period_range("1/1/2000", freq="90D", periods=3)
tdi = TimedeltaIndex(["-1 Day", "-1 Day", "-1 Day"])
tdarr = tdi.values
expected = period_range("12/31/1999", freq="90D", periods=3)
result = rng + tdi
tm.assert_index_equal(result, expected)
result = rng + tdarr
tm.assert_index_equal(result, expected)
result = tdi + rng
tm.assert_index_equal(result, expected)
result = tdarr + rng
tm.assert_index_equal(result, expected)
expected = period_range("1/2/2000", freq="90D", periods=3)
result = rng - tdi
tm.assert_index_equal(result, expected)
result = rng - tdarr
tm.assert_index_equal(result, expected)
msg = r"cannot subtract .* from .*"
with pytest.raises(TypeError, match=msg):
tdarr - rng
with pytest.raises(TypeError, match=msg):
tdi - rng
@pytest.mark.parametrize("pi_freq", ["D", "W", "Q", "H"])
@pytest.mark.parametrize("tdi_freq", [None, "H"])
def test_parr_sub_td64array(self, box_with_array, tdi_freq, pi_freq):
box = box_with_array
xbox = box if box not in [pd.array, tm.to_array] else pd.Index
tdi = TimedeltaIndex(["1 hours", "2 hours"], freq=tdi_freq)
dti = Timestamp("2018-03-07 17:16:40") + tdi
pi = dti.to_period(pi_freq)
# TODO: parametrize over box for pi?
td64obj = tm.box_expected(tdi, box)
if pi_freq == "H":
result = pi - td64obj
expected = (pi.to_timestamp("S") - tdi).to_period(pi_freq)
expected = tm.box_expected(expected, xbox)
tm.assert_equal(result, expected)
# Subtract from scalar
result = pi[0] - td64obj
expected = (pi[0].to_timestamp("S") - tdi).to_period(pi_freq)
expected = tm.box_expected(expected, box)
tm.assert_equal(result, expected)
elif pi_freq == "D":
# Tick, but non-compatible
msg = (
"Cannot add/subtract timedelta-like from PeriodArray that is "
"not an integer multiple of the PeriodArray's freq."
)
with pytest.raises(IncompatibleFrequency, match=msg):
pi - td64obj
with pytest.raises(IncompatibleFrequency, match=msg):
pi[0] - td64obj
else:
# With non-Tick freq, we could not add timedelta64 array regardless
# of what its resolution is
msg = "Cannot add or subtract timedelta64"
with pytest.raises(TypeError, match=msg):
pi - td64obj
with pytest.raises(TypeError, match=msg):
pi[0] - td64obj
# -----------------------------------------------------------------
# operations with array/Index of DateOffset objects
@pytest.mark.parametrize("box", [np.array, pd.Index])
def test_pi_add_offset_array(self, box):
# GH#18849
pi = PeriodIndex([Period("2015Q1"), Period("2016Q2")])
offs = box(
[
pd.offsets.QuarterEnd(n=1, startingMonth=12),
pd.offsets.QuarterEnd(n=-2, startingMonth=12),
]
)
expected = PeriodIndex([Period("2015Q2"), Period("2015Q4")]).astype(object)
with tm.assert_produces_warning(PerformanceWarning):
res = pi + offs
tm.assert_index_equal(res, expected)
with tm.assert_produces_warning(PerformanceWarning):
res2 = offs + pi
tm.assert_index_equal(res2, expected)
unanchored = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
# addition/subtraction ops with incompatible offsets should issue
# a PerformanceWarning and _then_ raise a TypeError.
msg = r"Input cannot be converted to Period\(freq=Q-DEC\)"
with pytest.raises(IncompatibleFrequency, match=msg):
with tm.assert_produces_warning(PerformanceWarning):
pi + unanchored
with pytest.raises(IncompatibleFrequency, match=msg):
with tm.assert_produces_warning(PerformanceWarning):
unanchored + pi
@pytest.mark.parametrize("box", [np.array, pd.Index])
def test_pi_sub_offset_array(self, box):
# GH#18824
pi = PeriodIndex([Period("2015Q1"), Period("2016Q2")])
other = box(
[
pd.offsets.QuarterEnd(n=1, startingMonth=12),
pd.offsets.QuarterEnd(n=-2, startingMonth=12),
]
)
expected = PeriodIndex([pi[n] - other[n] for n in range(len(pi))])
expected = expected.astype(object)
with tm.assert_produces_warning(PerformanceWarning):
res = pi - other
tm.assert_index_equal(res, expected)
anchored = box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
# addition/subtraction ops with anchored offsets should issue
# a PerformanceWarning and _then_ raise a TypeError.
msg = r"Input has different freq=-1M from Period\(freq=Q-DEC\)"
with pytest.raises(IncompatibleFrequency, match=msg):
with tm.assert_produces_warning(PerformanceWarning):
pi - anchored
with pytest.raises(IncompatibleFrequency, match=msg):
with tm.assert_produces_warning(PerformanceWarning):
anchored - pi
def test_pi_add_iadd_int(self, one):
# Variants of `one` for #19012
rng = period_range("2000-01-01 09:00", freq="H", periods=10)
result = rng + one
expected = period_range("2000-01-01 10:00", freq="H", periods=10)
tm.assert_index_equal(result, expected)
rng += one
tm.assert_index_equal(rng, expected)
def test_pi_sub_isub_int(self, one):
"""
PeriodIndex.__sub__ and __isub__ with several representations of
the integer 1, e.g. int, np.int64, np.uint8, ...
"""
rng = period_range("2000-01-01 09:00", freq="H", periods=10)
result = rng - one
expected = period_range("2000-01-01 08:00", freq="H", periods=10)
tm.assert_index_equal(result, expected)
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)
result = rng - five
exp = rng + (-five)
tm.assert_index_equal(result, exp)
def test_pi_add_sub_int_array_freqn_gt1(self):
# GH#47209 test adding array of ints when freq.n > 1 matches
# scalar behavior
pi = period_range("2016-01-01", periods=10, freq="2D")
arr = np.arange(10)
result = pi + arr
expected = pd.Index([x + y for x, y in zip(pi, arr)])
tm.assert_index_equal(result, expected)
result = pi - arr
expected = pd.Index([x - y for x, y in zip(pi, arr)])
tm.assert_index_equal(result, expected)
def test_pi_sub_isub_offset(self):
# offset
# DateOffset
rng = period_range("2014", "2024", freq="A")
result = rng - pd.offsets.YearEnd(5)
expected = period_range("2009", "2019", freq="A")
tm.assert_index_equal(result, expected)
rng -= pd.offsets.YearEnd(5)
tm.assert_index_equal(rng, expected)
rng = period_range("2014-01", "2016-12", freq="M")
result = rng - pd.offsets.MonthEnd(5)
expected = period_range("2013-08", "2016-07", freq="M")
tm.assert_index_equal(result, expected)
rng -= pd.offsets.MonthEnd(5)
tm.assert_index_equal(rng, expected)
@pytest.mark.parametrize("transpose", [True, False])
def test_pi_add_offset_n_gt1(self, box_with_array, transpose):
# GH#23215
# add offset to PeriodIndex with freq.n > 1
per = Period("2016-01", freq="2M")
pi = PeriodIndex([per])
expected = PeriodIndex(["2016-03"], freq="2M")
pi = tm.box_expected(pi, box_with_array, transpose=transpose)
expected = tm.box_expected(expected, box_with_array, transpose=transpose)
result = pi + per.freq
tm.assert_equal(result, expected)
result = per.freq + pi
tm.assert_equal(result, expected)
def test_pi_add_offset_n_gt1_not_divisible(self, box_with_array):
# GH#23215
# PeriodIndex with freq.n > 1 add offset with offset.n % freq.n != 0
pi = PeriodIndex(["2016-01"], freq="2M")
expected = PeriodIndex(["2016-04"], freq="2M")
pi = tm.box_expected(pi, box_with_array)
expected = tm.box_expected(expected, box_with_array)
result = pi + to_offset("3M")
tm.assert_equal(result, expected)
result = to_offset("3M") + pi
tm.assert_equal(result, expected)
# ---------------------------------------------------------------
# __add__/__sub__ with integer arrays
@pytest.mark.parametrize("int_holder", [np.array, pd.Index])
@pytest.mark.parametrize("op", [operator.add, ops.radd])
def test_pi_add_intarray(self, int_holder, op):
# GH#19959
pi = PeriodIndex([Period("2015Q1"), Period("NaT")])
other = int_holder([4, -1])
result = op(pi, other)
expected = PeriodIndex([Period("2016Q1"), Period("NaT")])
tm.assert_index_equal(result, expected)