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from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
import itertools
import numpy as np
import pytest
from pandas._config import using_pyarrow_string_dtype
from pandas.compat import (
IS64,
is_platform_windows,
)
from pandas.compat.numpy import np_version_gt2
import pandas as pd
import pandas._testing as tm
###############################################################
# Index / Series common tests which may trigger dtype coercions
###############################################################
@pytest.fixture(autouse=True, scope="class")
def check_comprehensiveness(request):
# Iterate over combination of dtype, method and klass
# and ensure that each are contained within a collected test
cls = request.cls
combos = itertools.product(cls.klasses, cls.dtypes, [cls.method])
def has_test(combo):
klass, dtype, method = combo
cls_funcs = request.node.session.items
return any(
klass in x.name and dtype in x.name and method in x.name for x in cls_funcs
)
opts = request.config.option
if opts.lf or opts.keyword:
# If we are running with "last-failed" or -k foo, we expect to only
# run a subset of tests.
yield
else:
for combo in combos:
if not has_test(combo):
raise AssertionError(
f"test method is not defined: {cls.__name__}, {combo}"
)
yield
class CoercionBase:
klasses = ["index", "series"]
dtypes = [
"object",
"int64",
"float64",
"complex128",
"bool",
"datetime64",
"datetime64tz",
"timedelta64",
"period",
]
@property
def method(self):
raise NotImplementedError(self)
class TestSetitemCoercion(CoercionBase):
method = "setitem"
# disable comprehensiveness tests, as most of these have been moved to
# tests.series.indexing.test_setitem in SetitemCastingEquivalents subclasses.
klasses: list[str] = []
def test_setitem_series_no_coercion_from_values_list(self):
# GH35865 - int casted to str when internally calling np.array(ser.values)
ser = pd.Series(["a", 1])
ser[:] = list(ser.values)
expected = pd.Series(["a", 1])
tm.assert_series_equal(ser, expected)
def _assert_setitem_index_conversion(
self, original_series, loc_key, expected_index, expected_dtype
):
"""test index's coercion triggered by assign key"""
temp = original_series.copy()
# GH#33469 pre-2.0 with int loc_key and temp.index.dtype == np.float64
# `temp[loc_key] = 5` treated loc_key as positional
temp[loc_key] = 5
exp = pd.Series([1, 2, 3, 4, 5], index=expected_index)
tm.assert_series_equal(temp, exp)
# check dtype explicitly for sure
assert temp.index.dtype == expected_dtype
temp = original_series.copy()
temp.loc[loc_key] = 5
exp = pd.Series([1, 2, 3, 4, 5], index=expected_index)
tm.assert_series_equal(temp, exp)
# check dtype explicitly for sure
assert temp.index.dtype == expected_dtype
@pytest.mark.parametrize(
"val,exp_dtype", [("x", object), (5, IndexError), (1.1, object)]
)
def test_setitem_index_object(self, val, exp_dtype):
obj = pd.Series([1, 2, 3, 4], index=pd.Index(list("abcd"), dtype=object))
assert obj.index.dtype == object
if exp_dtype is IndexError:
temp = obj.copy()
warn_msg = "Series.__setitem__ treating keys as positions is deprecated"
msg = "index 5 is out of bounds for axis 0 with size 4"
with pytest.raises(exp_dtype, match=msg):
with tm.assert_produces_warning(FutureWarning, match=warn_msg):
temp[5] = 5
else:
exp_index = pd.Index(list("abcd") + [val], dtype=object)
self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)
@pytest.mark.parametrize(
"val,exp_dtype", [(5, np.int64), (1.1, np.float64), ("x", object)]
)
def test_setitem_index_int64(self, val, exp_dtype):
obj = pd.Series([1, 2, 3, 4])
assert obj.index.dtype == np.int64
exp_index = pd.Index([0, 1, 2, 3, val])
self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)
@pytest.mark.parametrize(
"val,exp_dtype", [(5, np.float64), (5.1, np.float64), ("x", object)]
)
def test_setitem_index_float64(self, val, exp_dtype, request):
obj = pd.Series([1, 2, 3, 4], index=[1.1, 2.1, 3.1, 4.1])
assert obj.index.dtype == np.float64
exp_index = pd.Index([1.1, 2.1, 3.1, 4.1, val])
self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_series_period(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_complex128(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_bool(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_datetime64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_datetime64tz(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_timedelta64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_setitem_index_period(self):
raise NotImplementedError
class TestInsertIndexCoercion(CoercionBase):
klasses = ["index"]
method = "insert"
def _assert_insert_conversion(self, original, value, expected, expected_dtype):
"""test coercion triggered by insert"""
target = original.copy()
res = target.insert(1, value)
tm.assert_index_equal(res, expected)
assert res.dtype == expected_dtype
@pytest.mark.parametrize(
"insert, coerced_val, coerced_dtype",
[
(1, 1, object),
(1.1, 1.1, object),
(False, False, object),
("x", "x", object),
],
)
def test_insert_index_object(self, insert, coerced_val, coerced_dtype):
obj = pd.Index(list("abcd"), dtype=object)
assert obj.dtype == object
exp = pd.Index(["a", coerced_val, "b", "c", "d"], dtype=object)
self._assert_insert_conversion(obj, insert, exp, coerced_dtype)
@pytest.mark.parametrize(
"insert, coerced_val, coerced_dtype",
[
(1, 1, None),
(1.1, 1.1, np.float64),
(False, False, object), # GH#36319
("x", "x", object),
],
)
def test_insert_int_index(
self, any_int_numpy_dtype, insert, coerced_val, coerced_dtype
):
dtype = any_int_numpy_dtype
obj = pd.Index([1, 2, 3, 4], dtype=dtype)
coerced_dtype = coerced_dtype if coerced_dtype is not None else dtype
exp = pd.Index([1, coerced_val, 2, 3, 4], dtype=coerced_dtype)
self._assert_insert_conversion(obj, insert, exp, coerced_dtype)
@pytest.mark.parametrize(
"insert, coerced_val, coerced_dtype",
[
(1, 1.0, None),
# When float_numpy_dtype=float32, this is not the case
# see the correction below
(1.1, 1.1, np.float64),
(False, False, object), # GH#36319
("x", "x", object),
],
)
def test_insert_float_index(
self, float_numpy_dtype, insert, coerced_val, coerced_dtype
):
dtype = float_numpy_dtype
obj = pd.Index([1.0, 2.0, 3.0, 4.0], dtype=dtype)
coerced_dtype = coerced_dtype if coerced_dtype is not None else dtype
if np_version_gt2 and dtype == "float32" and coerced_val == 1.1:
# Hack, in the 2nd test case, since 1.1 can be losslessly cast to float32
# the expected dtype will be float32 if the original dtype was float32
coerced_dtype = np.float32
exp = pd.Index([1.0, coerced_val, 2.0, 3.0, 4.0], dtype=coerced_dtype)
self._assert_insert_conversion(obj, insert, exp, coerced_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[
(pd.Timestamp("2012-01-01"), "datetime64[ns]"),
(pd.Timestamp("2012-01-01", tz="US/Eastern"), "datetime64[ns, US/Eastern]"),
],
ids=["datetime64", "datetime64tz"],
)
@pytest.mark.parametrize(
"insert_value",
[pd.Timestamp("2012-01-01"), pd.Timestamp("2012-01-01", tz="Asia/Tokyo"), 1],
)
def test_insert_index_datetimes(self, fill_val, exp_dtype, insert_value):
obj = pd.DatetimeIndex(
["2011-01-01", "2011-01-02", "2011-01-03", "2011-01-04"], tz=fill_val.tz
).as_unit("ns")
assert obj.dtype == exp_dtype
exp = pd.DatetimeIndex(
["2011-01-01", fill_val.date(), "2011-01-02", "2011-01-03", "2011-01-04"],
tz=fill_val.tz,
).as_unit("ns")
self._assert_insert_conversion(obj, fill_val, exp, exp_dtype)
if fill_val.tz:
# mismatched tzawareness
ts = pd.Timestamp("2012-01-01")
result = obj.insert(1, ts)
expected = obj.astype(object).insert(1, ts)
assert expected.dtype == object
tm.assert_index_equal(result, expected)
ts = pd.Timestamp("2012-01-01", tz="Asia/Tokyo")
result = obj.insert(1, ts)
# once deprecation is enforced:
expected = obj.insert(1, ts.tz_convert(obj.dtype.tz))
assert expected.dtype == obj.dtype
tm.assert_index_equal(result, expected)
else:
# mismatched tzawareness
ts = pd.Timestamp("2012-01-01", tz="Asia/Tokyo")
result = obj.insert(1, ts)
expected = obj.astype(object).insert(1, ts)
assert expected.dtype == object
tm.assert_index_equal(result, expected)
item = 1
result = obj.insert(1, item)
expected = obj.astype(object).insert(1, item)
assert expected[1] == item
assert expected.dtype == object
tm.assert_index_equal(result, expected)
def test_insert_index_timedelta64(self):
obj = pd.TimedeltaIndex(["1 day", "2 day", "3 day", "4 day"])
assert obj.dtype == "timedelta64[ns]"
# timedelta64 + timedelta64 => timedelta64
exp = pd.TimedeltaIndex(["1 day", "10 day", "2 day", "3 day", "4 day"])
self._assert_insert_conversion(
obj, pd.Timedelta("10 day"), exp, "timedelta64[ns]"
)
for item in [pd.Timestamp("2012-01-01"), 1]:
result = obj.insert(1, item)
expected = obj.astype(object).insert(1, item)
assert expected.dtype == object
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize(
"insert, coerced_val, coerced_dtype",
[
(pd.Period("2012-01", freq="M"), "2012-01", "period[M]"),
(pd.Timestamp("2012-01-01"), pd.Timestamp("2012-01-01"), object),
(1, 1, object),
("x", "x", object),
],
)
def test_insert_index_period(self, insert, coerced_val, coerced_dtype):
obj = pd.PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq="M")
assert obj.dtype == "period[M]"
data = [
pd.Period("2011-01", freq="M"),
coerced_val,
pd.Period("2011-02", freq="M"),
pd.Period("2011-03", freq="M"),
pd.Period("2011-04", freq="M"),
]
if isinstance(insert, pd.Period):
exp = pd.PeriodIndex(data, freq="M")
self._assert_insert_conversion(obj, insert, exp, coerced_dtype)
# string that can be parsed to appropriate PeriodDtype
self._assert_insert_conversion(obj, str(insert), exp, coerced_dtype)
else:
result = obj.insert(0, insert)
expected = obj.astype(object).insert(0, insert)
tm.assert_index_equal(result, expected)
# TODO: ATM inserting '2012-01-01 00:00:00' when we have obj.freq=="M"
# casts that string to Period[M], not clear that is desirable
if not isinstance(insert, pd.Timestamp):
# non-castable string
result = obj.insert(0, str(insert))
expected = obj.astype(object).insert(0, str(insert))
tm.assert_index_equal(result, expected)
@pytest.mark.xfail(reason="Test not implemented")
def test_insert_index_complex128(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_insert_index_bool(self):
raise NotImplementedError
class TestWhereCoercion(CoercionBase):
method = "where"
_cond = np.array([True, False, True, False])
def _assert_where_conversion(
self, original, cond, values, expected, expected_dtype
):
"""test coercion triggered by where"""
target = original.copy()
res = target.where(cond, values)
tm.assert_equal(res, expected)
assert res.dtype == expected_dtype
def _construct_exp(self, obj, klass, fill_val, exp_dtype):
if fill_val is True:
values = klass([True, False, True, True])
elif isinstance(fill_val, (datetime, np.datetime64)):
values = pd.date_range(fill_val, periods=4)
else:
values = klass(x * fill_val for x in [5, 6, 7, 8])
exp = klass([obj[0], values[1], obj[2], values[3]], dtype=exp_dtype)
return values, exp
def _run_test(self, obj, fill_val, klass, exp_dtype):
cond = klass(self._cond)
exp = klass([obj[0], fill_val, obj[2], fill_val], dtype=exp_dtype)
self._assert_where_conversion(obj, cond, fill_val, exp, exp_dtype)
values, exp = self._construct_exp(obj, klass, fill_val, exp_dtype)
self._assert_where_conversion(obj, cond, values, exp, exp_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[(1, object), (1.1, object), (1 + 1j, object), (True, object)],
)
def test_where_object(self, index_or_series, fill_val, exp_dtype):
klass = index_or_series
obj = klass(list("abcd"), dtype=object)
assert obj.dtype == object
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[(1, np.int64), (1.1, np.float64), (1 + 1j, np.complex128), (True, object)],
)
def test_where_int64(self, index_or_series, fill_val, exp_dtype, request):
klass = index_or_series
obj = klass([1, 2, 3, 4])
assert obj.dtype == np.int64
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.parametrize(
"fill_val, exp_dtype",
[(1, np.float64), (1.1, np.float64), (1 + 1j, np.complex128), (True, object)],
)
def test_where_float64(self, index_or_series, fill_val, exp_dtype, request):
klass = index_or_series
obj = klass([1.1, 2.2, 3.3, 4.4])
assert obj.dtype == np.float64
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[
(1, np.complex128),
(1.1, np.complex128),
(1 + 1j, np.complex128),
(True, object),
],
)
def test_where_complex128(self, index_or_series, fill_val, exp_dtype):
klass = index_or_series
obj = klass([1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=np.complex128)
assert obj.dtype == np.complex128
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[(1, object), (1.1, object), (1 + 1j, object), (True, np.bool_)],
)
def test_where_series_bool(self, index_or_series, fill_val, exp_dtype):
klass = index_or_series
obj = klass([True, False, True, False])
assert obj.dtype == np.bool_
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.parametrize(
"fill_val,exp_dtype",
[
(pd.Timestamp("2012-01-01"), "datetime64[ns]"),
(pd.Timestamp("2012-01-01", tz="US/Eastern"), object),
],
ids=["datetime64", "datetime64tz"],
)
def test_where_datetime64(self, index_or_series, fill_val, exp_dtype):
klass = index_or_series
obj = klass(pd.date_range("2011-01-01", periods=4, freq="D")._with_freq(None))
assert obj.dtype == "datetime64[ns]"
fv = fill_val
# do the check with each of the available datetime scalars
if exp_dtype == "datetime64[ns]":
for scalar in [fv, fv.to_pydatetime(), fv.to_datetime64()]:
self._run_test(obj, scalar, klass, exp_dtype)
else:
for scalar in [fv, fv.to_pydatetime()]:
self._run_test(obj, fill_val, klass, exp_dtype)
@pytest.mark.xfail(reason="Test not implemented")
def test_where_index_complex128(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_where_index_bool(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_where_series_timedelta64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_where_series_period(self):
raise NotImplementedError
@pytest.mark.parametrize(
"value", [pd.Timedelta(days=9), timedelta(days=9), np.timedelta64(9, "D")]
)
def test_where_index_timedelta64(self, value):
tdi = pd.timedelta_range("1 Day", periods=4)
cond = np.array([True, False, False, True])
expected = pd.TimedeltaIndex(["1 Day", value, value, "4 Days"])
result = tdi.where(cond, value)
tm.assert_index_equal(result, expected)
# wrong-dtyped NaT
dtnat = np.datetime64("NaT", "ns")
expected = pd.Index([tdi[0], dtnat, dtnat, tdi[3]], dtype=object)
assert expected[1] is dtnat
result = tdi.where(cond, dtnat)
tm.assert_index_equal(result, expected)
def test_where_index_period(self):
dti = pd.date_range("2016-01-01", periods=3, freq="QS")
pi = dti.to_period("Q")
cond = np.array([False, True, False])
# Passing a valid scalar
value = pi[-1] + pi.freq * 10
expected = pd.PeriodIndex([value, pi[1], value])
result = pi.where(cond, value)
tm.assert_index_equal(result, expected)
# Case passing ndarray[object] of Periods
other = np.asarray(pi + pi.freq * 10, dtype=object)
result = pi.where(cond, other)
expected = pd.PeriodIndex([other[0], pi[1], other[2]])
tm.assert_index_equal(result, expected)
# Passing a mismatched scalar -> casts to object
td = pd.Timedelta(days=4)
expected = pd.Index([td, pi[1], td], dtype=object)
result = pi.where(cond, td)
tm.assert_index_equal(result, expected)
per = pd.Period("2020-04-21", "D")
expected = pd.Index([per, pi[1], per], dtype=object)
result = pi.where(cond, per)
tm.assert_index_equal(result, expected)
class TestFillnaSeriesCoercion(CoercionBase):
# not indexing, but place here for consistency
method = "fillna"
@pytest.mark.xfail(reason="Test not implemented")
def test_has_comprehensive_tests(self):
raise NotImplementedError
def _assert_fillna_conversion(self, original, value, expected, expected_dtype):
"""test coercion triggered by fillna"""
target = original.copy()
res = target.fillna(value)
tm.assert_equal(res, expected)
assert res.dtype == expected_dtype
@pytest.mark.parametrize(
"fill_val, fill_dtype",
[(1, object), (1.1, object), (1 + 1j, object), (True, object)],
)
def test_fillna_object(self, index_or_series, fill_val, fill_dtype):
klass = index_or_series
obj = klass(["a", np.nan, "c", "d"], dtype=object)
assert obj.dtype == object
exp = klass(["a", fill_val, "c", "d"], dtype=object)
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.parametrize(
"fill_val,fill_dtype",
[(1, np.float64), (1.1, np.float64), (1 + 1j, np.complex128), (True, object)],
)
def test_fillna_float64(self, index_or_series, fill_val, fill_dtype):
klass = index_or_series
obj = klass([1.1, np.nan, 3.3, 4.4])
assert obj.dtype == np.float64
exp = klass([1.1, fill_val, 3.3, 4.4])
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.parametrize(
"fill_val,fill_dtype",
[
(1, np.complex128),
(1.1, np.complex128),
(1 + 1j, np.complex128),
(True, object),
],
)
def test_fillna_complex128(self, index_or_series, fill_val, fill_dtype):
klass = index_or_series
obj = klass([1 + 1j, np.nan, 3 + 3j, 4 + 4j], dtype=np.complex128)
assert obj.dtype == np.complex128
exp = klass([1 + 1j, fill_val, 3 + 3j, 4 + 4j])
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.parametrize(
"fill_val,fill_dtype",
[
(pd.Timestamp("2012-01-01"), "datetime64[ns]"),
(pd.Timestamp("2012-01-01", tz="US/Eastern"), object),
(1, object),
("x", object),
],
ids=["datetime64", "datetime64tz", "object", "object"],
)
def test_fillna_datetime(self, index_or_series, fill_val, fill_dtype):
klass = index_or_series
obj = klass(
[
pd.Timestamp("2011-01-01"),
pd.NaT,
pd.Timestamp("2011-01-03"),
pd.Timestamp("2011-01-04"),
]
)
assert obj.dtype == "datetime64[ns]"
exp = klass(
[
pd.Timestamp("2011-01-01"),
fill_val,
pd.Timestamp("2011-01-03"),
pd.Timestamp("2011-01-04"),
]
)
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.parametrize(
"fill_val,fill_dtype",
[
(pd.Timestamp("2012-01-01", tz="US/Eastern"), "datetime64[ns, US/Eastern]"),
(pd.Timestamp("2012-01-01"), object),
# pre-2.0 with a mismatched tz we would get object result
(pd.Timestamp("2012-01-01", tz="Asia/Tokyo"), "datetime64[ns, US/Eastern]"),
(1, object),
("x", object),
],
)
def test_fillna_datetime64tz(self, index_or_series, fill_val, fill_dtype):
klass = index_or_series
tz = "US/Eastern"
obj = klass(
[
pd.Timestamp("2011-01-01", tz=tz),
pd.NaT,
pd.Timestamp("2011-01-03", tz=tz),
pd.Timestamp("2011-01-04", tz=tz),
]
)
assert obj.dtype == "datetime64[ns, US/Eastern]"
if getattr(fill_val, "tz", None) is None:
fv = fill_val
else:
fv = fill_val.tz_convert(tz)
exp = klass(
[
pd.Timestamp("2011-01-01", tz=tz),
fv,
pd.Timestamp("2011-01-03", tz=tz),
pd.Timestamp("2011-01-04", tz=tz),
]
)
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.parametrize(
"fill_val",
[
1,
1.1,
1 + 1j,
True,
pd.Interval(1, 2, closed="left"),
pd.Timestamp("2012-01-01", tz="US/Eastern"),
pd.Timestamp("2012-01-01"),
pd.Timedelta(days=1),
pd.Period("2016-01-01", "D"),
],
)
def test_fillna_interval(self, index_or_series, fill_val):
ii = pd.interval_range(1.0, 5.0, closed="right").insert(1, np.nan)
assert isinstance(ii.dtype, pd.IntervalDtype)
obj = index_or_series(ii)
exp = index_or_series([ii[0], fill_val, ii[2], ii[3], ii[4]], dtype=object)
fill_dtype = object
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_series_int64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_index_int64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_series_bool(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_index_bool(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_series_timedelta64(self):
raise NotImplementedError
@pytest.mark.parametrize(
"fill_val",
[
1,
1.1,
1 + 1j,
True,
pd.Interval(1, 2, closed="left"),
pd.Timestamp("2012-01-01", tz="US/Eastern"),
pd.Timestamp("2012-01-01"),
pd.Timedelta(days=1),
pd.Period("2016-01-01", "W"),
],
)
def test_fillna_series_period(self, index_or_series, fill_val):
pi = pd.period_range("2016-01-01", periods=4, freq="D").insert(1, pd.NaT)
assert isinstance(pi.dtype, pd.PeriodDtype)
obj = index_or_series(pi)
exp = index_or_series([pi[0], fill_val, pi[2], pi[3], pi[4]], dtype=object)
fill_dtype = object
self._assert_fillna_conversion(obj, fill_val, exp, fill_dtype)
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_index_timedelta64(self):
raise NotImplementedError
@pytest.mark.xfail(reason="Test not implemented")
def test_fillna_index_period(self):
raise NotImplementedError
class TestReplaceSeriesCoercion(CoercionBase):
klasses = ["series"]
method = "replace"
rep: dict[str, list] = {}
rep["object"] = ["a", "b"]
rep["int64"] = [4, 5]
rep["float64"] = [1.1, 2.2]
rep["complex128"] = [1 + 1j, 2 + 2j]
rep["bool"] = [True, False]
rep["datetime64[ns]"] = [pd.Timestamp("2011-01-01"), pd.Timestamp("2011-01-03")]
for tz in ["UTC", "US/Eastern"]:
# to test tz => different tz replacement
key = f"datetime64[ns, {tz}]"
rep[key] = [
pd.Timestamp("2011-01-01", tz=tz),
pd.Timestamp("2011-01-03", tz=tz),
]
rep["timedelta64[ns]"] = [pd.Timedelta("1 day"), pd.Timedelta("2 day")]
@pytest.fixture(params=["dict", "series"])
def how(self, request):
return request.param
@pytest.fixture(
params=[
"object",
"int64",
"float64",
"complex128",
"bool",
"datetime64[ns]",
"datetime64[ns, UTC]",
"datetime64[ns, US/Eastern]",
"timedelta64[ns]",
]
)
def from_key(self, request):
return request.param
@pytest.fixture(
params=[
"object",
"int64",
"float64",
"complex128",
"bool",
"datetime64[ns]",
"datetime64[ns, UTC]",
"datetime64[ns, US/Eastern]",
"timedelta64[ns]",
],
ids=[
"object",
"int64",
"float64",
"complex128",
"bool",
"datetime64",
"datetime64tz",
"datetime64tz",
"timedelta64",
],
)
def to_key(self, request):
return request.param
@pytest.fixture
def replacer(self, how, from_key, to_key):
"""
Object we will pass to `Series.replace`
"""
if how == "dict":
replacer = dict(zip(self.rep[from_key], self.rep[to_key]))
elif how == "series":
replacer = pd.Series(self.rep[to_key], index=self.rep[from_key])
else:
raise ValueError
return replacer
# Expected needs adjustment for the infer string option, seems to work as expecetd
@pytest.mark.skipif(using_pyarrow_string_dtype(), reason="TODO: test is to complex")
def test_replace_series(self, how, to_key, from_key, replacer):
index = pd.Index([3, 4], name="xxx")
obj = pd.Series(self.rep[from_key], index=index, name="yyy")
assert obj.dtype == from_key
if from_key.startswith("datetime") and to_key.startswith("datetime"):
# tested below
return
elif from_key in ["datetime64[ns, US/Eastern]", "datetime64[ns, UTC]"]:
# tested below
return
if (from_key == "float64" and to_key in ("int64")) or (
from_key == "complex128" and to_key in ("int64", "float64")
):
if not IS64 or is_platform_windows():
pytest.skip(f"32-bit platform buggy: {from_key} -> {to_key}")
# Expected: do not downcast by replacement
exp = pd.Series(self.rep[to_key], index=index, name="yyy", dtype=from_key)
else:
exp = pd.Series(self.rep[to_key], index=index, name="yyy")
assert exp.dtype == to_key
msg = "Downcasting behavior in `replace`"
warn = FutureWarning
if (
exp.dtype == obj.dtype
or exp.dtype == object
or (exp.dtype.kind in "iufc" and obj.dtype.kind in "iufc")
):
warn = None
with tm.assert_produces_warning(warn, match=msg):
result = obj.replace(replacer)
tm.assert_series_equal(result, exp)
@pytest.mark.parametrize(
"to_key",
["timedelta64[ns]", "bool", "object", "complex128", "float64", "int64"],
indirect=True,
)
@pytest.mark.parametrize(
"from_key", ["datetime64[ns, UTC]", "datetime64[ns, US/Eastern]"], indirect=True
)
def test_replace_series_datetime_tz(
self, how, to_key, from_key, replacer, using_infer_string
):
index = pd.Index([3, 4], name="xyz")
obj = pd.Series(self.rep[from_key], index=index, name="yyy")
assert obj.dtype == from_key
exp = pd.Series(self.rep[to_key], index=index, name="yyy")
if using_infer_string and to_key == "object":
assert exp.dtype == "string"
else:
assert exp.dtype == to_key
msg = "Downcasting behavior in `replace`"
warn = FutureWarning if exp.dtype != object else None
with tm.assert_produces_warning(warn, match=msg):
result = obj.replace(replacer)
tm.assert_series_equal(result, exp)
@pytest.mark.parametrize(
"to_key",
["datetime64[ns]", "datetime64[ns, UTC]", "datetime64[ns, US/Eastern]"],
indirect=True,
)
@pytest.mark.parametrize(
"from_key",
["datetime64[ns]", "datetime64[ns, UTC]", "datetime64[ns, US/Eastern]"],
indirect=True,
)
def test_replace_series_datetime_datetime(self, how, to_key, from_key, replacer):
index = pd.Index([3, 4], name="xyz")
obj = pd.Series(self.rep[from_key], index=index, name="yyy")
assert obj.dtype == from_key
exp = pd.Series(self.rep[to_key], index=index, name="yyy")
warn = FutureWarning
if isinstance(obj.dtype, pd.DatetimeTZDtype) and isinstance(
exp.dtype, pd.DatetimeTZDtype
):
# with mismatched tzs, we retain the original dtype as of 2.0
exp = exp.astype(obj.dtype)
warn = None
else:
assert exp.dtype == to_key
if to_key == from_key:
warn = None
msg = "Downcasting behavior in `replace`"
with tm.assert_produces_warning(warn, match=msg):
result = obj.replace(replacer)
tm.assert_series_equal(result, exp)
@pytest.mark.xfail(reason="Test not implemented")
def test_replace_series_period(self):
raise NotImplementedError
|