Alle Dateien aus dem Pythonkurs
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

612 lines
22 KiB

import numpy as np
import pytest
from pandas.errors import InvalidIndexError
from pandas import (
NA,
Index,
RangeIndex,
Series,
Timestamp,
)
import pandas._testing as tm
from pandas.core.arrays import (
ArrowExtensionArray,
FloatingArray,
)
@pytest.fixture
def index_large():
# 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 Index(large, dtype=np.uint64)
class TestGetLoc:
def test_get_loc(self):
index = Index([0, 1, 2])
assert index.get_loc(1) == 1
def test_get_loc_raises_bad_label(self):
index = Index([0, 1, 2])
with pytest.raises(InvalidIndexError, match=r"\[1, 2\]"):
index.get_loc([1, 2])
def test_get_loc_float64(self):
idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
with pytest.raises(KeyError, match="^'foo'$"):
idx.get_loc("foo")
with pytest.raises(KeyError, match=r"^1\.5$"):
idx.get_loc(1.5)
with pytest.raises(KeyError, match="^True$"):
idx.get_loc(True)
with pytest.raises(KeyError, match="^False$"):
idx.get_loc(False)
def test_get_loc_na(self):
idx = Index([np.nan, 1, 2], dtype=np.float64)
assert idx.get_loc(1) == 1
assert idx.get_loc(np.nan) == 0
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 = 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 = Index([1, 2], dtype=np.float64)
assert idx.get_loc(1) == 0
with pytest.raises(KeyError, match=r"^3$"):
idx.get_loc(3)
with pytest.raises(KeyError, match="^nan$"):
idx.get_loc(np.nan)
with pytest.raises(InvalidIndexError, match=r"\[nan\]"):
# listlike/non-hashable raises TypeError
idx.get_loc([np.nan])
@pytest.mark.parametrize("vals", [[1], [1.0], [Timestamp("2019-12-31")], ["test"]])
def test_get_loc_float_index_nan_with_method(self, vals):
# GH#39382
idx = Index(vals)
with pytest.raises(KeyError, match="nan"):
idx.get_loc(np.nan)
@pytest.mark.parametrize("dtype", ["f8", "i8", "u8"])
def test_get_loc_numericindex_none_raises(self, dtype):
# case that goes through searchsorted and key is non-comparable to values
arr = np.arange(10**7, dtype=dtype)
idx = Index(arr)
with pytest.raises(KeyError, match="None"):
idx.get_loc(None)
def test_get_loc_overflows(self):
# unique but non-monotonic goes through IndexEngine.mapping.get_item
idx = Index([0, 2, 1])
val = np.iinfo(np.int64).max + 1
with pytest.raises(KeyError, match=str(val)):
idx.get_loc(val)
with pytest.raises(KeyError, match=str(val)):
idx._engine.get_loc(val)
class TestGetIndexer:
def test_get_indexer(self):
index1 = Index([1, 2, 3, 4, 5])
index2 = Index([2, 4, 6])
r1 = index1.get_indexer(index2)
e1 = np.array([1, 3, -1], dtype=np.intp)
tm.assert_almost_equal(r1, e1)
@pytest.mark.parametrize("reverse", [True, False])
@pytest.mark.parametrize(
"expected,method",
[
(np.array([-1, 0, 0, 1, 1], dtype=np.intp), "pad"),
(np.array([-1, 0, 0, 1, 1], dtype=np.intp), "ffill"),
(np.array([0, 0, 1, 1, 2], dtype=np.intp), "backfill"),
(np.array([0, 0, 1, 1, 2], dtype=np.intp), "bfill"),
],
)
def test_get_indexer_methods(self, reverse, expected, method):
index1 = Index([1, 2, 3, 4, 5])
index2 = Index([2, 4, 6])
if reverse:
index1 = index1[::-1]
expected = expected[::-1]
result = index2.get_indexer(index1, method=method)
tm.assert_almost_equal(result, expected)
def test_get_indexer_invalid(self):
# GH10411
index = Index(np.arange(10))
with pytest.raises(ValueError, match="tolerance argument"):
index.get_indexer([1, 0], tolerance=1)
with pytest.raises(ValueError, match="limit argument"):
index.get_indexer([1, 0], limit=1)
@pytest.mark.parametrize(
"method, tolerance, indexer, expected",
[
("pad", None, [0, 5, 9], [0, 5, 9]),
("backfill", None, [0, 5, 9], [0, 5, 9]),
("nearest", None, [0, 5, 9], [0, 5, 9]),
("pad", 0, [0, 5, 9], [0, 5, 9]),
("backfill", 0, [0, 5, 9], [0, 5, 9]),
("nearest", 0, [0, 5, 9], [0, 5, 9]),
("pad", None, [0.2, 1.8, 8.5], [0, 1, 8]),
("backfill", None, [0.2, 1.8, 8.5], [1, 2, 9]),
("nearest", None, [0.2, 1.8, 8.5], [0, 2, 9]),
("pad", 1, [0.2, 1.8, 8.5], [0, 1, 8]),
("backfill", 1, [0.2, 1.8, 8.5], [1, 2, 9]),
("nearest", 1, [0.2, 1.8, 8.5], [0, 2, 9]),
("pad", 0.2, [0.2, 1.8, 8.5], [0, -1, -1]),
("backfill", 0.2, [0.2, 1.8, 8.5], [-1, 2, -1]),
("nearest", 0.2, [0.2, 1.8, 8.5], [0, 2, -1]),
],
)
def test_get_indexer_nearest(self, method, tolerance, indexer, expected):
index = Index(np.arange(10))
actual = index.get_indexer(indexer, method=method, tolerance=tolerance)
tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
@pytest.mark.parametrize("listtype", [list, tuple, Series, np.array])
@pytest.mark.parametrize(
"tolerance, expected",
list(
zip(
[[0.3, 0.3, 0.1], [0.2, 0.1, 0.1], [0.1, 0.5, 0.5]],
[[0, 2, -1], [0, -1, -1], [-1, 2, 9]],
)
),
)
def test_get_indexer_nearest_listlike_tolerance(
self, tolerance, expected, listtype
):
index = Index(np.arange(10))
actual = index.get_indexer(
[0.2, 1.8, 8.5], method="nearest", tolerance=listtype(tolerance)
)
tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
def test_get_indexer_nearest_error(self):
index = Index(np.arange(10))
with pytest.raises(ValueError, match="limit argument"):
index.get_indexer([1, 0], method="nearest", limit=1)
with pytest.raises(ValueError, match="tolerance size must match"):
index.get_indexer([1, 0], method="nearest", tolerance=[1, 2, 3])
@pytest.mark.parametrize(
"method,expected",
[("pad", [8, 7, 0]), ("backfill", [9, 8, 1]), ("nearest", [9, 7, 0])],
)
def test_get_indexer_nearest_decreasing(self, method, expected):
index = Index(np.arange(10))[::-1]
actual = index.get_indexer([0, 5, 9], method=method)
tm.assert_numpy_array_equal(actual, np.array([9, 4, 0], dtype=np.intp))
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_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_dtype):
# GH 16877
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)
expected = np.array([-1, -1, -1], dtype=np.intp)
if method == "get_indexer":
tm.assert_numpy_array_equal(result, expected)
else:
missing = np.arange(3, dtype=np.intp)
tm.assert_numpy_array_equal(result[0], expected)
tm.assert_numpy_array_equal(result[1], missing)
@pytest.mark.parametrize("method", ["pad", "backfill", "nearest"])
def test_get_indexer_with_method_numeric_vs_bool(self, method):
left = Index([1, 2, 3])
right = Index([True, False])
with pytest.raises(TypeError, match="Cannot compare"):
left.get_indexer(right, method=method)
with pytest.raises(TypeError, match="Cannot compare"):
right.get_indexer(left, method=method)
def test_get_indexer_numeric_vs_bool(self):
left = Index([1, 2, 3])
right = Index([True, False])
res = left.get_indexer(right)
expected = -1 * np.ones(len(right), dtype=np.intp)
tm.assert_numpy_array_equal(res, expected)
res = right.get_indexer(left)
expected = -1 * np.ones(len(left), dtype=np.intp)
tm.assert_numpy_array_equal(res, expected)
res = left.get_indexer_non_unique(right)[0]
expected = -1 * np.ones(len(right), dtype=np.intp)
tm.assert_numpy_array_equal(res, expected)
res = right.get_indexer_non_unique(left)[0]
expected = -1 * np.ones(len(left), dtype=np.intp)
tm.assert_numpy_array_equal(res, expected)
def test_get_indexer_float64(self):
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)
)
target = [-0.1, 0.5, 1.1]
tm.assert_numpy_array_equal(
idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
)
def test_get_indexer_nan(self):
# GH#7820
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 = 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 = 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 = 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 = 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 = 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 = 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)
@pytest.mark.parametrize("val, val2", [(4, 5), (4, 4), (4, NA), (NA, NA)])
def test_get_loc_masked(self, val, val2, any_numeric_ea_and_arrow_dtype):
# GH#39133
idx = Index([1, 2, 3, val, val2], dtype=any_numeric_ea_and_arrow_dtype)
result = idx.get_loc(2)
assert result == 1
with pytest.raises(KeyError, match="9"):
idx.get_loc(9)
def test_get_loc_masked_na(self, any_numeric_ea_and_arrow_dtype):
# GH#39133
idx = Index([1, 2, NA], dtype=any_numeric_ea_and_arrow_dtype)
result = idx.get_loc(NA)
assert result == 2
idx = Index([1, 2, NA, NA], dtype=any_numeric_ea_and_arrow_dtype)
result = idx.get_loc(NA)
tm.assert_numpy_array_equal(result, np.array([False, False, True, True]))
idx = Index([1, 2, 3], dtype=any_numeric_ea_and_arrow_dtype)
with pytest.raises(KeyError, match="NA"):
idx.get_loc(NA)
def test_get_loc_masked_na_and_nan(self):
# GH#39133
idx = Index(
FloatingArray(
np.array([1, 2, 1, np.nan]), mask=np.array([False, False, True, False])
)
)
result = idx.get_loc(NA)
assert result == 2
result = idx.get_loc(np.nan)
assert result == 3
idx = Index(
FloatingArray(np.array([1, 2, 1.0]), mask=np.array([False, False, True]))
)
result = idx.get_loc(NA)
assert result == 2
with pytest.raises(KeyError, match="nan"):
idx.get_loc(np.nan)
idx = Index(
FloatingArray(
np.array([1, 2, np.nan]), mask=np.array([False, False, False])
)
)
result = idx.get_loc(np.nan)
assert result == 2
with pytest.raises(KeyError, match="NA"):
idx.get_loc(NA)
@pytest.mark.parametrize("val", [4, 2])
def test_get_indexer_masked_na(self, any_numeric_ea_and_arrow_dtype, val):
# GH#39133
idx = Index([1, 2, NA, 3, val], dtype=any_numeric_ea_and_arrow_dtype)
result = idx.get_indexer_for([1, NA, 5])
expected = np.array([0, 2, -1])
tm.assert_numpy_array_equal(result, expected, check_dtype=False)
@pytest.mark.parametrize("dtype", ["boolean", "bool[pyarrow]"])
def test_get_indexer_masked_na_boolean(self, dtype):
# GH#39133
if dtype == "bool[pyarrow]":
pytest.importorskip("pyarrow")
idx = Index([True, False, NA], dtype=dtype)
result = idx.get_loc(False)
assert result == 1
result = idx.get_loc(NA)
assert result == 2
def test_get_indexer_arrow_dictionary_target(self):
pa = pytest.importorskip("pyarrow")
target = Index(
ArrowExtensionArray(
pa.array([1, 2], type=pa.dictionary(pa.int8(), pa.int8()))
)
)
idx = Index([1])
result = idx.get_indexer(target)
expected = np.array([0, -1], dtype=np.int64)
tm.assert_numpy_array_equal(result, expected)
result_1, result_2 = idx.get_indexer_non_unique(target)
expected_1, expected_2 = np.array([0, -1], dtype=np.int64), np.array(
[1], dtype=np.int64
)
tm.assert_numpy_array_equal(result_1, expected_1)
tm.assert_numpy_array_equal(result_2, expected_2)
class TestWhere:
@pytest.mark.parametrize(
"index",
[
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):
cond = [True] * len(index)
expected = index
result = index.where(listlike_box(cond))
cond = [False] + [True] * (len(index) - 1)
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 = Index([0, 6, 2], dtype=np.uint64)
mask = np.array([False, True, False])
other = np.array([1], dtype=np.int64)
expected = Index([1, 6, 1], dtype=np.uint64)
result = idx.where(mask, other)
tm.assert_index_equal(result, expected)
result = idx.putmask(~mask, other)
tm.assert_index_equal(result, expected)
def test_where_infers_type_instead_of_trying_to_convert_string_to_float(self):
# GH 32413
index = Index([1, np.nan])
cond = index.notna()
other = Index(["a", "b"], dtype="string")
expected = Index([1.0, "b"])
result = index.where(cond, other)
tm.assert_index_equal(result, expected)
class TestTake:
@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 = Index([1.0, 2.0, 3.0], name="xxx", dtype=np.float64)
result = idx.take(np.array([1, 0, -1]))
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 = 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 = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
tm.assert_index_equal(result, expected)
msg = (
"When allow_fill=True and fill_value is not None, "
"all indices must be >= -1"
)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
msg = "index -5 is out of bounds for (axis 0 with )?size 3"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))
@pytest.mark.parametrize("dtype", [np.int64, np.uint64])
def test_take_fill_value_ints(self, dtype):
# see gh-12631
idx = Index([1, 2, 3], dtype=dtype, name="xxx")
result = idx.take(np.array([1, 0, -1]))
expected = Index([2, 1, 3], dtype=dtype, name="xxx")
tm.assert_index_equal(result, expected)
name = type(idx).__name__
msg = f"Unable to fill values because {name} cannot contain NA"
# fill_value=True
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -1]), fill_value=True)
# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = Index([2, 1, 3], dtype=dtype, name="xxx")
tm.assert_index_equal(result, expected)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
msg = "index -5 is out of bounds for (axis 0 with )?size 3"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))
class TestContains:
@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 = Index([0, 1, 2, 3, 4], dtype=dtype)
assert None not in index
def test_contains_float64_nans(self):
index = Index([1.0, 2.0, np.nan], dtype=np.float64)
assert np.nan in index
def test_contains_float64_not_nans(self):
index = Index([1.0, 2.0, np.nan], dtype=np.float64)
assert 1.0 in index
class TestSliceLocs:
@pytest.mark.parametrize("dtype", [int, float])
def test_slice_locs(self, dtype):
index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
n = len(index)
assert index.slice_locs(start=2) == (2, n)
assert index.slice_locs(start=3) == (3, n)
assert index.slice_locs(3, 8) == (3, 6)
assert index.slice_locs(5, 10) == (3, n)
assert index.slice_locs(end=8) == (0, 6)
assert index.slice_locs(end=9) == (0, 7)
# reversed
index2 = index[::-1]
assert index2.slice_locs(8, 2) == (2, 6)
assert index2.slice_locs(7, 3) == (2, 5)
@pytest.mark.parametrize("dtype", [int, float])
def test_slice_locs_float_locs(self, dtype):
index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
n = len(index)
assert index.slice_locs(5.0, 10.0) == (3, n)
assert index.slice_locs(4.5, 10.5) == (3, 8)
index2 = index[::-1]
assert index2.slice_locs(8.5, 1.5) == (2, 6)
assert index2.slice_locs(10.5, -1) == (0, n)
@pytest.mark.parametrize("dtype", [int, float])
def test_slice_locs_dup_numeric(self, dtype):
index = Index(np.array([10, 12, 12, 14], dtype=dtype))
assert index.slice_locs(12, 12) == (1, 3)
assert index.slice_locs(11, 13) == (1, 3)
index2 = index[::-1]
assert index2.slice_locs(12, 12) == (1, 3)
assert index2.slice_locs(13, 11) == (1, 3)
def test_slice_locs_na(self):
index = Index([np.nan, 1, 2])
assert index.slice_locs(1) == (1, 3)
assert index.slice_locs(np.nan) == (0, 3)
index = Index([0, np.nan, np.nan, 1, 2])
assert index.slice_locs(np.nan) == (1, 5)
def test_slice_locs_na_raises(self):
index = Index([np.nan, 1, 2])
with pytest.raises(KeyError, match=""):
index.slice_locs(start=1.5)
with pytest.raises(KeyError, match=""):
index.slice_locs(end=1.5)
class TestGetSliceBounds:
@pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
def test_get_slice_bounds_within(self, side, expected):
index = Index(range(6))
result = index.get_slice_bound(4, side=side)
assert result == expected
@pytest.mark.parametrize("side", ["left", "right"])
@pytest.mark.parametrize("bound, expected", [(-1, 0), (10, 6)])
def test_get_slice_bounds_outside(self, side, expected, bound):
index = Index(range(6))
result = index.get_slice_bound(bound, side=side)
assert result == expected