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Nov 16, 2022
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DEPR: remove Int64Index, UInt64Index, Float64Index from tests.indexes.numeric #49682

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f423202
DEPR: remove Int64Index, UInt64Index, Float64Index from tests.indexes…
Nov 13, 2022
3b89c50
add back pylint
Nov 13, 2022
7f697c3
RangeIndex in test_indexing.py
Nov 14, 2022
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13 changes: 13 additions & 0 deletions pandas/tests/indexes/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -818,6 +818,19 @@ def test_can_hold_identifiers(self, simple_index):
key = idx[0]
assert idx._can_hold_identifiers_and_holds_name(key) is False

def test_view(self, dtype):
index_cls = self._index_cls

idx = index_cls([], dtype=dtype, name="Foo")
idx_view = idx.view()
assert idx_view.name == "Foo"

idx_view = idx.view(dtype)
tm.assert_index_equal(idx, index_cls(idx_view, name="Foo"), exact=True)

idx_view = idx.view(index_cls)
tm.assert_index_equal(idx, index_cls(idx_view, name="Foo"), exact=True)

def test_format(self, simple_index):
# GH35439
idx = simple_index
Expand Down
45 changes: 20 additions & 25 deletions pandas/tests/indexes/numeric/test_astype.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,72 +7,67 @@

from pandas import Index
import pandas._testing as tm
from pandas.core.indexes.api import (
Float64Index,
Int64Index,
UInt64Index,
)


class TestAstype:
def test_astype_float64_to_uint64(self):
# GH#45309 used to incorrectly return Int64Index
idx = Float64Index([0.0, 5.0, 10.0, 15.0, 20.0])
idx = Index([0.0, 5.0, 10.0, 15.0, 20.0], dtype=np.float64)
result = idx.astype("u8")
expected = UInt64Index([0, 5, 10, 15, 20])
tm.assert_index_equal(result, expected)
expected = Index([0, 5, 10, 15, 20], dtype=np.uint64)
tm.assert_index_equal(result, expected, exact=True)

idx_with_negatives = idx - 10
with pytest.raises(ValueError, match="losslessly"):
idx_with_negatives.astype(np.uint64)

def test_astype_float64_to_object(self):
float_index = Float64Index([0.0, 2.5, 5.0, 7.5, 10.0])
float_index = Index([0.0, 2.5, 5.0, 7.5, 10.0], dtype=np.float64)
result = float_index.astype(object)
assert result.equals(float_index)
assert float_index.equals(result)
assert isinstance(result, Index) and not isinstance(result, Float64Index)
assert isinstance(result, Index) and result.dtype == object

def test_astype_float64_mixed_to_object(self):
# mixed int-float
idx = Float64Index([1.5, 2, 3, 4, 5])
idx = Index([1.5, 2, 3, 4, 5], dtype=np.float64)
idx.name = "foo"
result = idx.astype(object)
assert result.equals(idx)
assert idx.equals(result)
assert isinstance(result, Index) and not isinstance(result, Float64Index)
assert isinstance(result, Index) and result.dtype == object

@pytest.mark.parametrize("dtype", ["int16", "int32", "int64"])
def test_astype_float64_to_int_dtype(self, dtype):
# GH#12881
# a float astype int
idx = Float64Index([0, 1, 2])
idx = Index([0, 1, 2], dtype=np.float64)
result = idx.astype(dtype)
expected = Int64Index([0, 1, 2])
tm.assert_index_equal(result, expected)
expected = Index([0, 1, 2], dtype=np.int64)
tm.assert_index_equal(result, expected, exact=True)

idx = Float64Index([0, 1.1, 2])
idx = Index([0, 1.1, 2], dtype=np.float64)
result = idx.astype(dtype)
expected = Int64Index([0, 1, 2])
tm.assert_index_equal(result, expected)
expected = Index([0, 1, 2], dtype=dtype)
tm.assert_index_equal(result, expected, exact=True)

@pytest.mark.parametrize("dtype", ["float32", "float64"])
def test_astype_float64_to_float_dtype(self, dtype):
# GH#12881
# a float astype int
idx = Float64Index([0, 1, 2])
idx = Index([0, 1, 2], dtype=np.float64)
result = idx.astype(dtype)
expected = idx
tm.assert_index_equal(result, expected)
tm.assert_index_equal(result, expected, exact=True)

idx = Float64Index([0, 1.1, 2])
idx = Index([0, 1.1, 2], dtype=np.float64)
result = idx.astype(dtype)
expected = Index(idx.values.astype(dtype))
tm.assert_index_equal(result, expected)
tm.assert_index_equal(result, expected, exact=True)

@pytest.mark.parametrize("dtype", ["M8[ns]", "m8[ns]"])
def test_cannot_cast_to_datetimelike(self, dtype):
idx = Float64Index([0, 1.1, 2])
idx = Index([0, 1.1, 2], dtype=np.float64)

msg = (
f"Cannot convert Float64Index to dtype {pandas_dtype(dtype)}; "
Expand All @@ -85,7 +80,7 @@ def test_cannot_cast_to_datetimelike(self, dtype):
@pytest.mark.parametrize("non_finite", [np.inf, np.nan])
def test_cannot_cast_inf_to_int(self, non_finite, dtype):
# GH#13149
idx = Float64Index([1, 2, non_finite])
idx = Index([1, 2, non_finite], dtype=np.float64)

msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
with pytest.raises(ValueError, match=msg):
Expand All @@ -94,6 +89,6 @@ def test_cannot_cast_inf_to_int(self, non_finite, dtype):
def test_astype_from_object(self):
index = Index([1.0, np.nan, 0.2], dtype="object")
result = index.astype(float)
expected = Float64Index([1.0, np.nan, 0.2])
expected = Index([1.0, np.nan, 0.2], dtype=np.float64)
assert result.dtype == expected.dtype
tm.assert_index_equal(result, expected)
97 changes: 47 additions & 50 deletions pandas/tests/indexes/numeric/test_indexing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,18 +10,13 @@
Timestamp,
)
import pandas._testing as tm
from pandas.core.indexes.api import (
Float64Index,
Int64Index,
UInt64Index,
)


@pytest.fixture
def index_large():
# large values used in UInt64Index tests where no compat needed with Int64/Float64
# large values used in Index[uint64] tests where no compat needed with Int64/Float64
large = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
return UInt64Index(large)
return Index(large, dtype=np.uint64)


class TestGetLoc:
Expand Down Expand Up @@ -86,7 +81,7 @@ def test_get_loc_raises_missized_tolerance(self):

@pytest.mark.filterwarnings("ignore:Passing method:FutureWarning")
def test_get_loc_float64(self):
idx = Float64Index([0.0, 1.0, 2.0])
idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
for method in [None, "pad", "backfill", "nearest"]:
assert idx.get_loc(1, method) == 1
if method is not None:
Expand Down Expand Up @@ -119,27 +114,27 @@ def test_get_loc_float64(self):
idx.get_loc(1.4, method="nearest", tolerance=np.array([1, 2]))

def test_get_loc_na(self):
idx = Float64Index([np.nan, 1, 2])
idx = Index([np.nan, 1, 2], dtype=np.float64)
assert idx.get_loc(1) == 1
assert idx.get_loc(np.nan) == 0

idx = Float64Index([np.nan, 1, np.nan])
idx = Index([np.nan, 1, np.nan], dtype=np.float64)
assert idx.get_loc(1) == 1

# representable by slice [0:2:2]
msg = "'Cannot get left slice bound for non-unique label: nan'"
with pytest.raises(KeyError, match=msg):
idx.slice_locs(np.nan)
# not representable by slice
idx = Float64Index([np.nan, 1, np.nan, np.nan])
idx = Index([np.nan, 1, np.nan, np.nan], dtype=np.float64)
assert idx.get_loc(1) == 1
msg = "'Cannot get left slice bound for non-unique label: nan"
with pytest.raises(KeyError, match=msg):
idx.slice_locs(np.nan)

def test_get_loc_missing_nan(self):
# GH#8569
idx = Float64Index([1, 2])
idx = Index([1, 2], dtype=np.float64)
assert idx.get_loc(1) == 0
with pytest.raises(KeyError, match=r"^3$"):
idx.get_loc(3)
Expand Down Expand Up @@ -285,14 +280,16 @@ def test_get_indexer_nearest_decreasing(self, method, expected):
actual = index.get_indexer([0.2, 1.8, 8.5], method=method)
tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))

@pytest.mark.parametrize(
"idx_class", [Int64Index, RangeIndex, Float64Index, UInt64Index]
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do the RangeIndex cases need to be added back somewhere?

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Good catch. I'll work something into this take this into account.

)
@pytest.mark.parametrize("idx_dtype", ["int64", "float64", "uint64", "range"])
@pytest.mark.parametrize("method", ["get_indexer", "get_indexer_non_unique"])
def test_get_indexer_numeric_index_boolean_target(self, method, idx_class):
def test_get_indexer_numeric_index_boolean_target(self, method, idx_dtype):
# GH 16877

numeric_index = idx_class(RangeIndex(4))
if idx_dtype == "range":
numeric_index = RangeIndex(4)
else:
numeric_index = Index(np.arange(4, dtype=idx_dtype))

other = Index([True, False, True])

result = getattr(numeric_index, method)(other)
Expand Down Expand Up @@ -336,7 +333,7 @@ def test_get_indexer_numeric_vs_bool(self):
tm.assert_numpy_array_equal(res, expected)

def test_get_indexer_float64(self):
idx = Float64Index([0.0, 1.0, 2.0])
idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
tm.assert_numpy_array_equal(
idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)
)
Expand All @@ -354,39 +351,39 @@ def test_get_indexer_float64(self):

def test_get_indexer_nan(self):
# GH#7820
result = Float64Index([1, 2, np.nan]).get_indexer([np.nan])
result = Index([1, 2, np.nan], dtype=np.float64).get_indexer([np.nan])
expected = np.array([2], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)

def test_get_indexer_int64(self):
index = Int64Index(range(0, 20, 2))
target = Int64Index(np.arange(10))
index = Index(range(0, 20, 2), dtype=np.int64)
target = Index(np.arange(10), dtype=np.int64)
indexer = index.get_indexer(target)
expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = Int64Index(np.arange(10))
target = Index(np.arange(10), dtype=np.int64)
indexer = index.get_indexer(target, method="pad")
expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = Int64Index(np.arange(10))
target = Index(np.arange(10), dtype=np.int64)
indexer = index.get_indexer(target, method="backfill")
expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

def test_get_indexer_uint64(self, index_large):
target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
indexer = index_large.get_indexer(target)
expected = np.array([0, -1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
indexer = index_large.get_indexer(target, method="pad")
expected = np.array([0, 0, 1, 2, 3, 4, 4, 4, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
indexer = index_large.get_indexer(target, method="backfill")
expected = np.array([0, 1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
Expand All @@ -396,9 +393,9 @@ class TestWhere:
@pytest.mark.parametrize(
"index",
[
Float64Index(np.arange(5, dtype="float64")),
Int64Index(range(0, 20, 2)),
UInt64Index(np.arange(5, dtype="uint64")),
Index(np.arange(5, dtype="float64")),
Index(range(0, 20, 2), dtype=np.int64),
Index(np.arange(5, dtype="uint64")),
],
)
def test_where(self, listlike_box, index):
Expand All @@ -407,16 +404,16 @@ def test_where(self, listlike_box, index):
result = index.where(listlike_box(cond))

cond = [False] + [True] * (len(index) - 1)
expected = Float64Index([index._na_value] + index[1:].tolist())
expected = Index([index._na_value] + index[1:].tolist(), dtype=np.float64)
result = index.where(listlike_box(cond))
tm.assert_index_equal(result, expected)

def test_where_uint64(self):
idx = UInt64Index([0, 6, 2])
idx = Index([0, 6, 2], dtype=np.uint64)
mask = np.array([False, True, False])
other = np.array([1], dtype=np.int64)

expected = UInt64Index([1, 6, 1])
expected = Index([1, 6, 1], dtype=np.uint64)

result = idx.where(mask, other)
tm.assert_index_equal(result, expected)
Expand All @@ -437,27 +434,27 @@ def test_where_infers_type_instead_of_trying_to_convert_string_to_float(self):


class TestTake:
@pytest.mark.parametrize("klass", [Float64Index, Int64Index, UInt64Index])
def test_take_preserve_name(self, klass):
index = klass([1, 2, 3, 4], name="foo")
@pytest.mark.parametrize("idx_dtype", [np.float64, np.int64, np.uint64])
def test_take_preserve_name(self, idx_dtype):
index = Index([1, 2, 3, 4], dtype=idx_dtype, name="foo")
taken = index.take([3, 0, 1])
assert index.name == taken.name

def test_take_fill_value_float64(self):
# GH 12631
idx = Float64Index([1.0, 2.0, 3.0], name="xxx")
idx = Index([1.0, 2.0, 3.0], name="xxx", dtype=np.float64)
result = idx.take(np.array([1, 0, -1]))
expected = Float64Index([2.0, 1.0, 3.0], name="xxx")
expected = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
tm.assert_index_equal(result, expected)

# fill_value
result = idx.take(np.array([1, 0, -1]), fill_value=True)
expected = Float64Index([2.0, 1.0, np.nan], name="xxx")
expected = Index([2.0, 1.0, np.nan], dtype=np.float64, name="xxx")
tm.assert_index_equal(result, expected)

# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = Float64Index([2.0, 1.0, 3.0], name="xxx")
expected = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
tm.assert_index_equal(result, expected)

msg = (
Expand All @@ -473,15 +470,15 @@ def test_take_fill_value_float64(self):
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))

@pytest.mark.parametrize("klass", [Int64Index, UInt64Index])
def test_take_fill_value_ints(self, klass):
@pytest.mark.parametrize("dtype", [np.int64, np.uint64])
def test_take_fill_value_ints(self, dtype):
# see gh-12631
idx = klass([1, 2, 3], name="xxx")
idx = Index([1, 2, 3], dtype=dtype, name="xxx")
result = idx.take(np.array([1, 0, -1]))
expected = klass([2, 1, 3], name="xxx")
expected = Index([2, 1, 3], dtype=dtype, name="xxx")
tm.assert_index_equal(result, expected)

name = klass.__name__
name = type(idx).__name__
msg = f"Unable to fill values because {name} cannot contain NA"

# fill_value=True
Expand All @@ -490,7 +487,7 @@ def test_take_fill_value_ints(self, klass):

# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = klass([2, 1, 3], name="xxx")
expected = Index([2, 1, 3], dtype=dtype, name="xxx")
tm.assert_index_equal(result, expected)

with pytest.raises(ValueError, match=msg):
Expand All @@ -504,18 +501,18 @@ def test_take_fill_value_ints(self, klass):


class TestContains:
@pytest.mark.parametrize("klass", [Float64Index, Int64Index, UInt64Index])
def test_contains_none(self, klass):
@pytest.mark.parametrize("dtype", [np.float64, np.int64, np.uint64])
def test_contains_none(self, dtype):
# GH#35788 should return False, not raise TypeError
index = klass([0, 1, 2, 3, 4])
index = Index([0, 1, 2, 3, 4], dtype=dtype)
assert None not in index

def test_contains_float64_nans(self):
index = Float64Index([1.0, 2.0, np.nan])
index = Index([1.0, 2.0, np.nan], dtype=np.float64)
assert np.nan in index

def test_contains_float64_not_nans(self):
index = Float64Index([1.0, 2.0, np.nan])
index = Index([1.0, 2.0, np.nan], dtype=np.float64)
assert 1.0 in index


Expand Down
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