craftbeerpi4-pione/venv/lib/python3.8/site-packages/pandas/tests/arithmetic/test_period.py
2021-01-30 22:29:33 +01:00

1534 lines
55 KiB
Python

# 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, TimedeltaIndex, period_range
import pandas._testing as tm
from pandas.core import ops
from pandas.core.arrays import TimedeltaArray
from .common import assert_invalid_comparison
# ------------------------------------------------------------------
# Comparisons
class TestPeriodArrayLikeComparisons:
# Comparison tests for PeriodDtype vectors fully parametrized over
# DataFrame/Series/PeriodIndex/PeriodArray. Ideally all comparison
# tests will eventually end up here.
def test_compare_zerodim(self, box_with_array):
# GH#26689 make sure we unbox zero-dimensional arrays
xbox = box_with_array if box_with_array is not pd.Index else np.ndarray
pi = pd.period_range("2000", periods=4)
other = np.array(pi.to_numpy()[0])
pi = tm.box_expected(pi, box_with_array)
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", pd.Timestamp.now(), pd.Timedelta(days=4)]
)
def test_compare_invalid_scalar(self, box_with_array, scalar):
# comparison with scalar that cannot be interpreted as a Period
pi = pd.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)),
],
)
def test_compare_invalid_listlike(self, box_with_array, other):
pi = pd.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 = pd.period_range("2000", periods=5)
parr = tm.box_expected(pi, box_with_array)
xbox = np.ndarray if box_with_array is pd.Index else box_with_array
other = other_box(pi)
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
@pytest.mark.parametrize("other", ["2017", pd.Period("2017", freq="D")])
def test_eq(self, other):
idx = PeriodIndex(["2017", "2017", "2018"], freq="D")
expected = np.array([True, True, False])
result = idx == other
tm.assert_numpy_array_equal(result, expected)
@pytest.mark.parametrize(
"other",
[
2017,
[2017, 2017, 2017],
np.array([2017, 2017, 2017]),
np.array([2017, 2017, 2017], dtype=object),
pd.Index([2017, 2017, 2017]),
],
)
def test_eq_integer_disallowed(self, other):
# match Period semantics by not treating integers as Periods
idx = PeriodIndex(["2017", "2017", "2018"], freq="D")
expected = np.array([False, False, False])
result = idx == other
tm.assert_numpy_array_equal(result, expected)
msg = "|".join(
[
"not supported between instances of 'Period' and 'int'",
r"Invalid comparison between dtype=period\[D\] and ",
]
)
with pytest.raises(TypeError, match=msg):
idx < other
with pytest.raises(TypeError, match=msg):
idx > other
with pytest.raises(TypeError, match=msg):
idx <= other
with pytest.raises(TypeError, match=msg):
idx >= other
def test_pi_cmp_period(self):
idx = period_range("2007-01", periods=20, freq="M")
result = idx < idx[10]
exp = idx.values < idx.values[10]
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):
xbox = box_with_array if box_with_array is not pd.Index else np.ndarray
pi = pd.period_range("2000-01-01", periods=10, freq="D")
val = Period("2000-01-04", freq="D")
expected = [x > val for x in pi]
ser = tm.box_expected(pi, box_with_array)
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
xbox = np.ndarray if box_with_array is pd.Index else box_with_array
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)
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
xbox = np.ndarray if box_with_array is pd.Index else box_with_array
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)
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_raises(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 = "Input has different freq=A-DEC from "
with pytest.raises(IncompatibleFrequency, match=msg):
base <= Period("2011", freq="A")
with pytest.raises(IncompatibleFrequency, 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"Input has different freq=(M|2M|3M) from PeriodArray\(freq=A-DEC\)"
idx_msg = rev_msg if box_with_array is tm.to_array else msg
with pytest.raises(IncompatibleFrequency, match=idx_msg):
base <= idx
# Different frequency
msg = "Input has different freq=4M from "
with pytest.raises(IncompatibleFrequency, match=msg):
base <= Period("2011", freq="4M")
with pytest.raises(IncompatibleFrequency, match=msg):
Period("2011", freq="4M") >= base
idx = PeriodIndex(["2011", "2012", "2013", "2014"], freq="4M")
rev_msg = r"Input has different freq=(M|2M|3M) from PeriodArray\(freq=4M\)"
idx_msg = rev_msg if box_with_array is tm.to_array else msg
with pytest.raises(IncompatibleFrequency, 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)
result = idx1 > Period("2011-02", freq=freq)
exp = np.array([False, False, False, True])
tm.assert_numpy_array_equal(result, exp)
result = Period("2011-02", freq=freq) < idx1
tm.assert_numpy_array_equal(result, exp)
result = idx1 == Period("NaT", freq=freq)
exp = np.array([False, False, False, False])
tm.assert_numpy_array_equal(result, exp)
result = Period("NaT", freq=freq) == idx1
tm.assert_numpy_array_equal(result, exp)
result = idx1 != Period("NaT", freq=freq)
exp = np.array([True, True, True, True])
tm.assert_numpy_array_equal(result, exp)
result = Period("NaT", freq=freq) != 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 = "Input has different freq=4M from Period(Array|Index)"
with pytest.raises(IncompatibleFrequency, match=msg):
idx1 > diff
with pytest.raises(IncompatibleFrequency, match=msg):
idx1 == diff
# TODO: De-duplicate with test_pi_cmp_nat
@pytest.mark.parametrize("dtype", [object, None])
def test_comp_nat(self, dtype):
left = pd.PeriodIndex(
[pd.Period("2011-01-01"), pd.NaT, pd.Period("2011-01-03")]
)
right = pd.PeriodIndex([pd.NaT, pd.NaT, pd.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 = pd.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 = pd.Series(values)
result = func(s)
exp = pd.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"
)
f = lambda x: x == pd.Period("2011-03", freq="M")
exp = np.array([False, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") == x
self._check(idx, f, exp)
f = lambda x: x != pd.Period("2011-03", freq="M")
exp = np.array([True, True, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") != x
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") >= x
exp = np.array([True, True, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: x > pd.Period("2011-03", freq="M")
exp = np.array([False, False, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") >= 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"
)
f = lambda x: x == pd.Period("2011-03", freq="M")
exp = np.array([False, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") == 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 != pd.Period("2011-03", freq="M")
exp = np.array([True, True, False, True], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: pd.Period("2011-03", freq="M") != 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: pd.Period("2011-03", freq="M") >= x
exp = np.array([True, False, True, False], dtype=np.bool_)
self._check(idx, f, exp)
f = lambda x: x < pd.Period("2011-03", freq="M")
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": [pd.Period("2015-01", freq="M"), pd.Period("2015-02", freq="M")],
"B": [pd.Period("2014-01", freq="M"), pd.Period("2014-02", freq="M")],
}
)
assert df["A"].dtype == "Period[M]"
assert df["B"].dtype == "Period[M]"
p = pd.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": [pd.Period("2015-05", freq="M"), pd.Period("2015-06", freq="M")],
"B": [pd.Period("2015-05", freq="M"), pd.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 = pd.period_range("1/1/2000", freq="D", periods=5)
other = pd.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 = pd.period_range("1/1/2000", freq="D", periods=5)
other = pd.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 = pd.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):
rng = pd.period_range("1/1/2000", freq="D", periods=5)
other = pd.period_range("1/6/2000", freq="H", periods=5)
# TODO: parametrize over boxes for other?
rng = tm.box_expected(rng, box_with_array)
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 = pd.PeriodIndex([p1_d], freq=tick_classes(n))
p2 = pd.PeriodIndex([p2_d], freq=tick_classes(n))
expected = pd.PeriodIndex([p2_d], freq=p2.freq.base) - pd.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 = pd.PeriodIndex([p1_d], freq=freq)
p2 = pd.PeriodIndex([p2_d], freq=freq)
result = p2 - p1
expected = pd.PeriodIndex([p2_d], freq=freq.base) - pd.PeriodIndex(
[p1_d], freq=freq.base
)
tm.assert_index_equal(result, expected)
# -------------------------------------------------------------
# Invalid Operations
@pytest.mark.parametrize("other", [3.14, np.array([2.0, 3.0])])
@pytest.mark.parametrize("op", [operator.add, ops.radd, operator.sub, ops.rsub])
def test_parr_add_sub_float_raises(self, op, other, box_with_array):
dti = pd.DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
pi = dti.to_period("D")
pi = tm.box_expected(pi, box_with_array)
msg = (
r"unsupported operand type\(s\) for [+-]: .* and .*|"
"Concatenation operation is not implemented for NumPy arrays"
)
with pytest.raises(TypeError, match=msg):
op(pi, other)
@pytest.mark.parametrize(
"other",
[
# datetime scalars
pd.Timestamp.now(),
pd.Timestamp.now().to_pydatetime(),
pd.Timestamp.now().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
],
)
def test_parr_add_sub_invalid(self, other, box_with_array):
# GH#23215
rng = pd.period_range("1/1/2000", freq="D", periods=3)
rng = tm.box_expected(rng, box_with_array)
msg = (
r"(:?cannot add PeriodArray and .*)"
r"|(:?cannot subtract .* from (:?a\s)?.*)"
r"|(:?unsupported operand type\(s\) for \+: .* and .*)"
)
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 = pd.period_range("1/1/2000", freq="Q", periods=3)
tdi = pd.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 timedelta64\[ns\]"
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 = pd.period_range("1/1/2000", freq="90D", periods=3)
tdi = pd.TimedeltaIndex(["-1 Day", "-1 Day", "-1 Day"])
tdarr = tdi.values
expected = pd.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 = pd.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 is not 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 = "Input has different freq=None from PeriodArray"
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 = pd.PeriodIndex([pd.Period("2015Q1"), pd.Period("2016Q2")])
offs = box(
[
pd.offsets.QuarterEnd(n=1, startingMonth=12),
pd.offsets.QuarterEnd(n=-2, startingMonth=12),
]
)
expected = pd.PeriodIndex([pd.Period("2015Q2"), pd.Period("2015Q4")])
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 = pd.PeriodIndex([pd.Period("2015Q1"), pd.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))])
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 = pd.period_range("2000-01-01 09:00", freq="H", periods=10)
result = rng + one
expected = pd.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 = pd.period_range("2000-01-01 09:00", freq="H", periods=10)
result = rng - one
expected = pd.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_sub_isub_offset(self):
# offset
# DateOffset
rng = pd.period_range("2014", "2024", freq="A")
result = rng - pd.offsets.YearEnd(5)
expected = pd.period_range("2009", "2019", freq="A")
tm.assert_index_equal(result, expected)
rng -= pd.offsets.YearEnd(5)
tm.assert_index_equal(rng, expected)
rng = pd.period_range("2014-01", "2016-12", freq="M")
result = rng - pd.offsets.MonthEnd(5)
expected = pd.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 = pd.Period("2016-01", freq="2M")
pi = pd.PeriodIndex([per])
expected = pd.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 = pd.PeriodIndex(["2016-01"], freq="2M")
expected = pd.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 = pd.PeriodIndex([pd.Period("2015Q1"), pd.Period("NaT")])
other = int_holder([4, -1])
result = op(pi, other)
expected = pd.PeriodIndex([pd.Period("2016Q1"), pd.Period("NaT")])
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize("int_holder", [np.array, pd.Index])
def test_pi_sub_intarray(self, int_holder):
# GH#19959
pi = pd.PeriodIndex([pd.Period("2015Q1"), pd.Period("NaT")])
other = int_holder([4, -1])
result = pi - other
expected = pd.PeriodIndex([pd.Period("2014Q1"), pd.Period("NaT")])
tm.assert_index_equal(result, expected)
msg = r"bad operand type for unary -: 'PeriodArray'"
with pytest.raises(TypeError, match=msg):
other - pi
# ---------------------------------------------------------------
# Timedelta-like (timedelta, timedelta64, Timedelta, Tick)
# TODO: Some of these are misnomers because of non-Tick DateOffsets
def test_pi_add_timedeltalike_minute_gt1(self, three_days):
# GH#23031 adding a time-delta-like offset to a PeriodArray that has
# minute frequency with n != 1. A more general case is tested below
# in test_pi_add_timedeltalike_tick_gt1, but here we write out the
# expected result more explicitly.
other = three_days
rng = pd.period_range("2014-05-01", periods=3, freq="2D")
expected = pd.PeriodIndex(["2014-05-04", "2014-05-06", "2014-05-08"], freq="2D")
result = rng + other
tm.assert_index_equal(result, expected)
result = other + rng
tm.assert_index_equal(result, expected)
# subtraction
expected = pd.PeriodIndex(["2014-04-28", "2014-04-30", "2014-05-02"], freq="2D")
result = rng - other
tm.assert_index_equal(result, expected)
msg = (
r"(:?bad operand type for unary -: 'PeriodArray')"
r"|(:?cannot subtract PeriodArray from timedelta64\[[hD]\])"
)
with pytest.raises(TypeError, match=msg):
other - rng
@pytest.mark.parametrize("freqstr", ["5ns", "5us", "5ms", "5s", "5T", "5h", "5d"])
def test_pi_add_timedeltalike_tick_gt1(self, three_days, freqstr):
# GH#23031 adding a time-delta-like offset to a PeriodArray that has
# tick-like frequency with n != 1
other = three_days
rng = pd.period_range("2014-05-01", periods=6, freq=freqstr)
expected = pd.period_range(rng[0] + other, periods=6, freq=freqstr)
result = rng + other
tm.assert_index_equal(result, expected)
result = other + rng
tm.assert_index_equal(result, expected)
# subtraction
expected = pd.period_range(rng[0] - other, periods=6, freq=freqstr)
result = rng - other
tm.assert_index_equal(result, expected)
msg = (
r"(:?bad operand type for unary -: 'PeriodArray')"
r"|(:?cannot subtract PeriodArray from timedelta64\[[hD]\])"
)
with pytest.raises(TypeError, match=msg):
other - rng
def test_pi_add_iadd_timedeltalike_daily(self, three_days):
# Tick
other = three_days
rng = pd.period_range("2014-05-01", "2014-05-15", freq="D")
expected = pd.period_range("2014-05-04", "2014-05-18", freq="D")
result = rng + other
tm.assert_index_equal(result, expected)
rng += other
tm.assert_index_equal(rng, expected)
def test_pi_sub_isub_timedeltalike_daily(self, three_days):
# Tick-like 3 Days
other = three_days
rng = pd.period_range("2014-05-01", "2014-05-15", freq="D")
expected = pd.period_range("2014-04-28", "2014-05-12", freq="D")
result = rng - other
tm.assert_index_equal(result, expected)
rng -= other
tm.assert_index_equal(rng, expected)
def test_pi_add_sub_timedeltalike_freq_mismatch_daily(self, not_daily):
other = not_daily
rng = pd.period_range("2014-05-01", "2014-05-15", freq="D")
msg = "Input has different freq(=.+)? from Period.*?\\(freq=D\\)"
with pytest.raises(IncompatibleFrequency, match=msg):
rng + other
with pytest.raises(IncompatibleFrequency, match=msg):
rng += other
with pytest.raises(IncompatibleFrequency, match=msg):
rng - other
with pytest.raises(IncompatibleFrequency, match=msg):
rng -= other
def test_pi_add_iadd_timedeltalike_hourly(self, two_hours):
other = two_hours
rng = pd.period_range("2014-01-01 10:00", "2014-01-05 10:00", freq="H")
expected = pd.period_range("2014-01-01 12:00", "2014-01-05 12:00", freq="H")
result = rng + other
tm.assert_index_equal(result, expected)
rng += other
tm.assert_index_equal(rng, expected)
def test_pi_add_timedeltalike_mismatched_freq_hourly(self, not_hourly):
other = not_hourly
rng = pd.period_range("2014-01-01 10:00", "2014-01-05 10:00", freq="H")
msg = "Input has different freq(=.+)? from Period.*?\\(freq=H\\)"
with pytest.raises(IncompatibleFrequency, match=msg):
rng + other
with pytest.raises(IncompatibleFrequency, match=msg):
rng += other
def test_pi_sub_isub_timedeltalike_hourly(self, two_hours):
other = two_hours
rng = pd.period_range("2014-01-01 10:00", "2014-01-05 10:00", freq="H")
expected = pd.period_range("2014-01-01 08:00", "2014-01-05 08:00", freq="H")
result = rng - other
tm.assert_index_equal(result, expected)
rng -= other
tm.assert_index_equal(rng, expected)
def test_add_iadd_timedeltalike_annual(self):
# offset
# DateOffset
rng = pd.period_range("2014", "2024", freq="A")
result = rng + pd.offsets.YearEnd(5)
expected = pd.period_range("2019", "2029", freq="A")
tm.assert_index_equal(result, expected)
rng += pd.offsets.YearEnd(5)
tm.assert_index_equal(rng, expected)
def test_pi_add_sub_timedeltalike_freq_mismatch_annual(self, mismatched_freq):
other = mismatched_freq
rng = pd.period_range("2014", "2024", freq="A")
msg = "Input has different freq(=.+)? from Period.*?\\(freq=A-DEC\\)"
with pytest.raises(IncompatibleFrequency, match=msg):
rng + other
with pytest.raises(IncompatibleFrequency, match=msg):
rng += other
with pytest.raises(IncompatibleFrequency, match=msg):
rng - other
with pytest.raises(IncompatibleFrequency, match=msg):
rng -= other
def test_pi_add_iadd_timedeltalike_M(self):
rng = pd.period_range("2014-01", "2016-12", freq="M")
expected = pd.period_range("2014-06", "2017-05", freq="M")
result = rng + pd.offsets.MonthEnd(5)
tm.assert_index_equal(result, expected)
rng += pd.offsets.MonthEnd(5)
tm.assert_index_equal(rng, expected)
def test_pi_add_sub_timedeltalike_freq_mismatch_monthly(self, mismatched_freq):
other = mismatched_freq
rng = pd.period_range("2014-01", "2016-12", freq="M")
msg = "Input has different freq(=.+)? from Period.*?\\(freq=M\\)"
with pytest.raises(IncompatibleFrequency, match=msg):
rng + other
with pytest.raises(IncompatibleFrequency, match=msg):
rng += other
with pytest.raises(IncompatibleFrequency, match=msg):
rng - other
with pytest.raises(IncompatibleFrequency, match=msg):
rng -= other
@pytest.mark.parametrize("transpose", [True, False])
def test_parr_add_sub_td64_nat(self, box_with_array, transpose):
# GH#23320 special handling for timedelta64("NaT")
pi = pd.period_range("1994-04-01", periods=9, freq="19D")
other = np.timedelta64("NaT")
expected = pd.PeriodIndex(["NaT"] * 9, freq="19D")
obj = tm.box_expected(pi, box_with_array, transpose=transpose)
expected = tm.box_expected(expected, box_with_array, transpose=transpose)
result = obj + other
tm.assert_equal(result, expected)
result = other + obj
tm.assert_equal(result, expected)
result = obj - other
tm.assert_equal(result, expected)
msg = r"cannot subtract .* from .*"
with pytest.raises(TypeError, match=msg):
other - obj
@pytest.mark.parametrize(
"other",
[
np.array(["NaT"] * 9, dtype="m8[ns]"),
TimedeltaArray._from_sequence(["NaT"] * 9),
],
)
def test_parr_add_sub_tdt64_nat_array(self, box_with_array, other):
pi = pd.period_range("1994-04-01", periods=9, freq="19D")
expected = pd.PeriodIndex(["NaT"] * 9, freq="19D")
obj = tm.box_expected(pi, box_with_array)
expected = tm.box_expected(expected, box_with_array)
result = obj + other
tm.assert_equal(result, expected)
result = other + obj
tm.assert_equal(result, expected)
result = obj - other
tm.assert_equal(result, expected)
msg = r"cannot subtract .* from .*"
with pytest.raises(TypeError, match=msg):
other - obj
# ---------------------------------------------------------------
# Unsorted
def test_parr_add_sub_index(self):
# Check that PeriodArray defers to Index on arithmetic ops
pi = pd.period_range("2000-12-31", periods=3)
parr = pi.array
result = parr - pi
expected = pi - pi
tm.assert_index_equal(result, expected)
def test_parr_add_sub_object_array(self):
pi = pd.period_range("2000-12-31", periods=3, freq="D")
parr = pi.array
other = np.array([pd.Timedelta(days=1), pd.offsets.Day(2), 3])
with tm.assert_produces_warning(PerformanceWarning):
result = parr + other
expected = pd.PeriodIndex(
["2001-01-01", "2001-01-03", "2001-01-05"], freq="D"
).array
tm.assert_equal(result, expected)
with tm.assert_produces_warning(PerformanceWarning):
result = parr - other
expected = pd.PeriodIndex(["2000-12-30"] * 3, freq="D").array
tm.assert_equal(result, expected)
class TestPeriodSeriesArithmetic:
def test_ops_series_timedelta(self):
# GH#13043
ser = pd.Series(
[pd.Period("2015-01-01", freq="D"), pd.Period("2015-01-02", freq="D")],
name="xxx",
)
assert ser.dtype == "Period[D]"
expected = pd.Series(
[pd.Period("2015-01-02", freq="D"), pd.Period("2015-01-03", freq="D")],
name="xxx",
)
result = ser + pd.Timedelta("1 days")
tm.assert_series_equal(result, expected)
result = pd.Timedelta("1 days") + ser
tm.assert_series_equal(result, expected)
result = ser + pd.tseries.offsets.Day()
tm.assert_series_equal(result, expected)
result = pd.tseries.offsets.Day() + ser
tm.assert_series_equal(result, expected)
def test_ops_series_period(self):
# GH#13043
ser = pd.Series(
[pd.Period("2015-01-01", freq="D"), pd.Period("2015-01-02", freq="D")],
name="xxx",
)
assert ser.dtype == "Period[D]"
per = pd.Period("2015-01-10", freq="D")
off = per.freq
# dtype will be object because of original dtype
expected = pd.Series([9 * off, 8 * off], name="xxx", dtype=object)
tm.assert_series_equal(per - ser, expected)
tm.assert_series_equal(ser - per, -1 * expected)
s2 = pd.Series(
[pd.Period("2015-01-05", freq="D"), pd.Period("2015-01-04", freq="D")],
name="xxx",
)
assert s2.dtype == "Period[D]"
expected = pd.Series([4 * off, 2 * off], name="xxx", dtype=object)
tm.assert_series_equal(s2 - ser, expected)
tm.assert_series_equal(ser - s2, -1 * expected)
class TestPeriodIndexSeriesMethods:
""" Test PeriodIndex and Period Series Ops consistency """
def _check(self, values, func, expected):
idx = pd.PeriodIndex(values)
result = func(idx)
tm.assert_equal(result, expected)
ser = pd.Series(values)
result = func(ser)
exp = pd.Series(expected, name=values.name)
tm.assert_series_equal(result, exp)
def test_pi_ops(self):
idx = PeriodIndex(
["2011-01", "2011-02", "2011-03", "2011-04"], freq="M", name="idx"
)
expected = PeriodIndex(
["2011-03", "2011-04", "2011-05", "2011-06"], freq="M", name="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
exp = pd.Index([0 * off, 1 * off, 2 * off, 3 * off], name="idx")
tm.assert_index_equal(result, exp)
result = Period("2011-01", freq="M") - idx
exp = pd.Index([0 * off, -1 * off, -2 * off, -3 * off], name="idx")
tm.assert_index_equal(result, exp)
@pytest.mark.parametrize("ng", ["str", 1.5])
@pytest.mark.parametrize(
"func",
[
lambda obj, ng: obj + ng,
lambda obj, ng: ng + obj,
lambda obj, ng: obj - ng,
lambda obj, ng: ng - obj,
lambda obj, ng: np.add(obj, ng),
lambda obj, ng: np.add(ng, obj),
lambda obj, ng: np.subtract(obj, ng),
lambda obj, ng: np.subtract(ng, obj),
],
)
def test_parr_ops_errors(self, ng, func, box_with_array):
idx = PeriodIndex(
["2011-01", "2011-02", "2011-03", "2011-04"], freq="M", name="idx"
)
obj = tm.box_expected(idx, box_with_array)
msg = (
r"unsupported operand type\(s\)|can only concatenate|"
r"must be str|object to str implicitly"
)
with pytest.raises(TypeError, match=msg):
func(obj, ng)
def test_pi_ops_nat(self):
idx = PeriodIndex(
["2011-01", "2011-02", "NaT", "2011-04"], freq="M", name="idx"
)
expected = PeriodIndex(
["2011-03", "2011-04", "NaT", "2011-06"], freq="M", name="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"
)
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):
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", "2011-04-01"],
freq="D",
name="idx",
)
f = lambda x: x + pd.offsets.Day()
exp = PeriodIndex(
["2011-01-02", "2011-02-02", "2011-03-02", "2011-04-02"],
freq="D",
name="idx",
)
self._check(idx, f, exp)
f = lambda x: x + pd.offsets.Day(2)
exp = PeriodIndex(
["2011-01-03", "2011-02-03", "2011-03-03", "2011-04-03"],
freq="D",
name="idx",
)
self._check(idx, f, exp)
f = lambda x: x - pd.offsets.Day(2)
exp = PeriodIndex(
["2010-12-30", "2011-01-30", "2011-02-27", "2011-03-30"],
freq="D",
name="idx",
)
self._check(idx, f, exp)
def test_pi_offset_errors(self):
idx = PeriodIndex(
["2011-01-01", "2011-02-01", "2011-03-01", "2011-04-01"],
freq="D",
name="idx",
)
ser = pd.Series(idx)
# Series op is applied per Period instance, thus error is raised
# from Period
for obj in [idx, ser]:
msg = r"Input has different freq=2H from Period.*?\(freq=D\)"
with pytest.raises(IncompatibleFrequency, match=msg):
obj + pd.offsets.Hour(2)
with pytest.raises(IncompatibleFrequency, match=msg):
pd.offsets.Hour(2) + obj
msg = r"Input has different freq=-2H from Period.*?\(freq=D\)"
with pytest.raises(IncompatibleFrequency, match=msg):
obj - pd.offsets.Hour(2)
def test_pi_sub_period(self):
# GH#13071
idx = PeriodIndex(
["2011-01", "2011-02", "2011-03", "2011-04"], freq="M", name="idx"
)
result = idx - pd.Period("2012-01", freq="M")
off = idx.freq
exp = pd.Index([-12 * off, -11 * off, -10 * off, -9 * off], name="idx")
tm.assert_index_equal(result, exp)
result = np.subtract(idx, pd.Period("2012-01", freq="M"))
tm.assert_index_equal(result, exp)
result = pd.Period("2012-01", freq="M") - idx
exp = pd.Index([12 * off, 11 * off, 10 * off, 9 * off], name="idx")
tm.assert_index_equal(result, exp)
result = np.subtract(pd.Period("2012-01", freq="M"), idx)
tm.assert_index_equal(result, exp)
exp = pd.TimedeltaIndex([np.nan, np.nan, np.nan, np.nan], name="idx")
result = idx - pd.Period("NaT", freq="M")
tm.assert_index_equal(result, exp)
assert result.freq == exp.freq
result = pd.Period("NaT", freq="M") - idx
tm.assert_index_equal(result, exp)
assert result.freq == exp.freq
def test_pi_sub_pdnat(self):
# GH#13071
idx = PeriodIndex(
["2011-01", "2011-02", "NaT", "2011-04"], freq="M", name="idx"
)
exp = pd.TimedeltaIndex([pd.NaT] * 4, name="idx")
tm.assert_index_equal(pd.NaT - idx, exp)
tm.assert_index_equal(idx - pd.NaT, exp)
def test_pi_sub_period_nat(self):
# GH#13071
idx = PeriodIndex(
["2011-01", "NaT", "2011-03", "2011-04"], freq="M", name="idx"
)
result = idx - pd.Period("2012-01", freq="M")
off = idx.freq
exp = pd.Index([-12 * off, pd.NaT, -10 * off, -9 * off], name="idx")
tm.assert_index_equal(result, exp)
result = pd.Period("2012-01", freq="M") - idx
exp = pd.Index([12 * off, pd.NaT, 10 * off, 9 * off], name="idx")
tm.assert_index_equal(result, exp)
exp = pd.TimedeltaIndex([np.nan, np.nan, np.nan, np.nan], name="idx")
tm.assert_index_equal(idx - pd.Period("NaT", freq="M"), exp)
tm.assert_index_equal(pd.Period("NaT", freq="M") - idx, exp)
@pytest.mark.parametrize("scalars", ["a", False, 1, 1.0, None])
def test_comparison_operations(self, scalars):
# GH 28980
expected = Series([False, False])
s = Series([pd.Period("2019"), pd.Period("2020")], dtype="period[A-DEC]")
result = s == scalars
tm.assert_series_equal(result, expected)