"""
|
test_indexing tests the following Index methods:
|
__getitem__
|
get_loc
|
get_value
|
__contains__
|
take
|
where
|
get_indexer
|
get_indexer_for
|
slice_locs
|
asof_locs
|
|
The corresponding tests.indexes.[index_type].test_indexing files
|
contain tests for the corresponding methods specific to those Index subclasses.
|
"""
|
import numpy as np
|
import pytest
|
|
from pandas.errors import InvalidIndexError
|
|
from pandas.core.dtypes.common import (
|
is_float_dtype,
|
is_scalar,
|
)
|
|
from pandas import (
|
NA,
|
DatetimeIndex,
|
Index,
|
IntervalIndex,
|
MultiIndex,
|
NaT,
|
PeriodIndex,
|
TimedeltaIndex,
|
)
|
import pandas._testing as tm
|
|
|
class TestTake:
|
def test_take_invalid_kwargs(self, index):
|
indices = [1, 2]
|
|
msg = r"take\(\) got an unexpected keyword argument 'foo'"
|
with pytest.raises(TypeError, match=msg):
|
index.take(indices, foo=2)
|
|
msg = "the 'out' parameter is not supported"
|
with pytest.raises(ValueError, match=msg):
|
index.take(indices, out=indices)
|
|
msg = "the 'mode' parameter is not supported"
|
with pytest.raises(ValueError, match=msg):
|
index.take(indices, mode="clip")
|
|
def test_take(self, index):
|
indexer = [4, 3, 0, 2]
|
if len(index) < 5:
|
# not enough elements; ignore
|
return
|
|
result = index.take(indexer)
|
expected = index[indexer]
|
assert result.equals(expected)
|
|
if not isinstance(index, (DatetimeIndex, PeriodIndex, TimedeltaIndex)):
|
# GH 10791
|
msg = r"'(.*Index)' object has no attribute 'freq'"
|
with pytest.raises(AttributeError, match=msg):
|
index.freq
|
|
def test_take_indexer_type(self):
|
# GH#42875
|
integer_index = Index([0, 1, 2, 3])
|
scalar_index = 1
|
msg = "Expected indices to be array-like"
|
with pytest.raises(TypeError, match=msg):
|
integer_index.take(scalar_index)
|
|
def test_take_minus1_without_fill(self, index):
|
# -1 does not get treated as NA unless allow_fill=True is passed
|
if len(index) == 0:
|
# Test is not applicable
|
return
|
|
result = index.take([0, 0, -1])
|
|
expected = index.take([0, 0, len(index) - 1])
|
tm.assert_index_equal(result, expected)
|
|
|
class TestContains:
|
@pytest.mark.parametrize(
|
"index,val",
|
[
|
(Index([0, 1, 2]), 2),
|
(Index([0, 1, "2"]), "2"),
|
(Index([0, 1, 2, np.inf, 4]), 4),
|
(Index([0, 1, 2, np.nan, 4]), 4),
|
(Index([0, 1, 2, np.inf]), np.inf),
|
(Index([0, 1, 2, np.nan]), np.nan),
|
],
|
)
|
def test_index_contains(self, index, val):
|
assert val in index
|
|
@pytest.mark.parametrize(
|
"index,val",
|
[
|
(Index([0, 1, 2]), "2"),
|
(Index([0, 1, "2"]), 2),
|
(Index([0, 1, 2, np.inf]), 4),
|
(Index([0, 1, 2, np.nan]), 4),
|
(Index([0, 1, 2, np.inf]), np.nan),
|
(Index([0, 1, 2, np.nan]), np.inf),
|
# Checking if np.inf in int64 Index should not cause an OverflowError
|
# Related to GH 16957
|
(Index([0, 1, 2], dtype=np.int64), np.inf),
|
(Index([0, 1, 2], dtype=np.int64), np.nan),
|
(Index([0, 1, 2], dtype=np.uint64), np.inf),
|
(Index([0, 1, 2], dtype=np.uint64), np.nan),
|
],
|
)
|
def test_index_not_contains(self, index, val):
|
assert val not in index
|
|
@pytest.mark.parametrize(
|
"index,val", [(Index([0, 1, "2"]), 0), (Index([0, 1, "2"]), "2")]
|
)
|
def test_mixed_index_contains(self, index, val):
|
# GH#19860
|
assert val in index
|
|
@pytest.mark.parametrize(
|
"index,val", [(Index([0, 1, "2"]), "1"), (Index([0, 1, "2"]), 2)]
|
)
|
def test_mixed_index_not_contains(self, index, val):
|
# GH#19860
|
assert val not in index
|
|
def test_contains_with_float_index(self, any_real_numpy_dtype):
|
# GH#22085
|
dtype = any_real_numpy_dtype
|
data = [0, 1, 2, 3] if not is_float_dtype(dtype) else [0.1, 1.1, 2.2, 3.3]
|
index = Index(data, dtype=dtype)
|
|
if not is_float_dtype(index.dtype):
|
assert 1.1 not in index
|
assert 1.0 in index
|
assert 1 in index
|
else:
|
assert 1.1 in index
|
assert 1.0 not in index
|
assert 1 not in index
|
|
def test_contains_requires_hashable_raises(self, index):
|
if isinstance(index, MultiIndex):
|
return # TODO: do we want this to raise?
|
|
msg = "unhashable type: 'list'"
|
with pytest.raises(TypeError, match=msg):
|
[] in index
|
|
msg = "|".join(
|
[
|
r"unhashable type: 'dict'",
|
r"must be real number, not dict",
|
r"an integer is required",
|
r"\{\}",
|
r"pandas\._libs\.interval\.IntervalTree' is not iterable",
|
]
|
)
|
with pytest.raises(TypeError, match=msg):
|
{} in index._engine
|
|
|
class TestGetLoc:
|
def test_get_loc_non_hashable(self, index):
|
# MultiIndex and Index raise TypeError, others InvalidIndexError
|
|
with pytest.raises((TypeError, InvalidIndexError), match="slice"):
|
index.get_loc(slice(0, 1))
|
|
def test_get_loc_non_scalar_hashable(self, index):
|
# GH52877
|
from enum import Enum
|
|
class E(Enum):
|
X1 = "x1"
|
|
assert not is_scalar(E.X1)
|
|
exc = KeyError
|
msg = "<E.X1: 'x1'>"
|
if isinstance(
|
index,
|
(
|
DatetimeIndex,
|
TimedeltaIndex,
|
PeriodIndex,
|
IntervalIndex,
|
),
|
):
|
# TODO: make these more consistent?
|
exc = InvalidIndexError
|
msg = "E.X1"
|
with pytest.raises(exc, match=msg):
|
index.get_loc(E.X1)
|
|
def test_get_loc_generator(self, index):
|
exc = KeyError
|
if isinstance(
|
index,
|
(
|
DatetimeIndex,
|
TimedeltaIndex,
|
PeriodIndex,
|
IntervalIndex,
|
MultiIndex,
|
),
|
):
|
# TODO: make these more consistent?
|
exc = InvalidIndexError
|
with pytest.raises(exc, match="generator object"):
|
# MultiIndex specifically checks for generator; others for scalar
|
index.get_loc(x for x in range(5))
|
|
def test_get_loc_masked_duplicated_na(self):
|
# GH#48411
|
idx = Index([1, 2, NA, NA], dtype="Int64")
|
result = idx.get_loc(NA)
|
expected = np.array([False, False, True, True])
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
class TestGetIndexer:
|
def test_get_indexer_base(self, index):
|
if index._index_as_unique:
|
expected = np.arange(index.size, dtype=np.intp)
|
actual = index.get_indexer(index)
|
tm.assert_numpy_array_equal(expected, actual)
|
else:
|
msg = "Reindexing only valid with uniquely valued Index objects"
|
with pytest.raises(InvalidIndexError, match=msg):
|
index.get_indexer(index)
|
|
with pytest.raises(ValueError, match="Invalid fill method"):
|
index.get_indexer(index, method="invalid")
|
|
def test_get_indexer_consistency(self, index):
|
# See GH#16819
|
|
if index._index_as_unique:
|
indexer = index.get_indexer(index[0:2])
|
assert isinstance(indexer, np.ndarray)
|
assert indexer.dtype == np.intp
|
else:
|
msg = "Reindexing only valid with uniquely valued Index objects"
|
with pytest.raises(InvalidIndexError, match=msg):
|
index.get_indexer(index[0:2])
|
|
indexer, _ = index.get_indexer_non_unique(index[0:2])
|
assert isinstance(indexer, np.ndarray)
|
assert indexer.dtype == np.intp
|
|
def test_get_indexer_masked_duplicated_na(self):
|
# GH#48411
|
idx = Index([1, 2, NA, NA], dtype="Int64")
|
result = idx.get_indexer_for(Index([1, NA], dtype="Int64"))
|
expected = np.array([0, 2, 3], dtype=result.dtype)
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
class TestConvertSliceIndexer:
|
def test_convert_almost_null_slice(self, index):
|
# slice with None at both ends, but not step
|
|
key = slice(None, None, "foo")
|
|
if isinstance(index, IntervalIndex):
|
msg = "label-based slicing with step!=1 is not supported for IntervalIndex"
|
with pytest.raises(ValueError, match=msg):
|
index._convert_slice_indexer(key, "loc")
|
else:
|
msg = "'>=' not supported between instances of 'str' and 'int'"
|
with pytest.raises(TypeError, match=msg):
|
index._convert_slice_indexer(key, "loc")
|
|
|
class TestPutmask:
|
def test_putmask_with_wrong_mask(self, index):
|
# GH#18368
|
if not len(index):
|
return
|
|
fill = index[0]
|
|
msg = "putmask: mask and data must be the same size"
|
with pytest.raises(ValueError, match=msg):
|
index.putmask(np.ones(len(index) + 1, np.bool_), fill)
|
|
with pytest.raises(ValueError, match=msg):
|
index.putmask(np.ones(len(index) - 1, np.bool_), fill)
|
|
with pytest.raises(ValueError, match=msg):
|
index.putmask("foo", fill)
|
|
|
@pytest.mark.parametrize(
|
"idx", [Index([1, 2, 3]), Index([0.1, 0.2, 0.3]), Index(["a", "b", "c"])]
|
)
|
def test_getitem_deprecated_float(idx):
|
# https://github.com/pandas-dev/pandas/issues/34191
|
|
msg = "Indexing with a float is no longer supported"
|
with pytest.raises(IndexError, match=msg):
|
idx[1.0]
|
|
|
@pytest.mark.parametrize(
|
"idx,target,expected",
|
[
|
([np.nan, "var1", np.nan], [np.nan], np.array([0, 2], dtype=np.intp)),
|
(
|
[np.nan, "var1", np.nan],
|
[np.nan, "var1"],
|
np.array([0, 2, 1], dtype=np.intp),
|
),
|
(
|
np.array([np.nan, "var1", np.nan], dtype=object),
|
[np.nan],
|
np.array([0, 2], dtype=np.intp),
|
),
|
(
|
DatetimeIndex(["2020-08-05", NaT, NaT]),
|
[NaT],
|
np.array([1, 2], dtype=np.intp),
|
),
|
(["a", "b", "a", np.nan], [np.nan], np.array([3], dtype=np.intp)),
|
(
|
np.array(["b", np.nan, float("NaN"), "b"], dtype=object),
|
Index([np.nan], dtype=object),
|
np.array([1, 2], dtype=np.intp),
|
),
|
],
|
)
|
def test_get_indexer_non_unique_multiple_nans(idx, target, expected):
|
# GH 35392
|
axis = Index(idx)
|
actual = axis.get_indexer_for(target)
|
tm.assert_numpy_array_equal(actual, expected)
|
|
|
def test_get_indexer_non_unique_nans_in_object_dtype_target(nulls_fixture):
|
idx = Index([1.0, 2.0])
|
target = Index([1, nulls_fixture], dtype="object")
|
|
result_idx, result_missing = idx.get_indexer_non_unique(target)
|
tm.assert_numpy_array_equal(result_idx, np.array([0, -1], dtype=np.intp))
|
tm.assert_numpy_array_equal(result_missing, np.array([1], dtype=np.intp))
|
