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leene
2025-09-07 22:09:54 +02:00
parent e1b817252c
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lib/python3.11/site-packages/pandas/tests/indexes/string/__init__.py Normal file
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lib/python3.11/site-packages/pandas/tests/indexes/string/test_astype.py Normal file
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from pandas import (
Index,
Series,
)
import pandas._testing as tm
def test_astype_str_from_bytes():
# https://github.com/pandas-dev/pandas/issues/38607
# GH#49658 pre-2.0 Index called .values.astype(str) here, which effectively
# did a .decode() on the bytes object. In 2.0 we go through
# ensure_string_array which does f"{val}"
idx = Index(["あ", b"a"], dtype="object")
result = idx.astype(str)
expected = Index(["あ", "a"], dtype="str")
tm.assert_index_equal(result, expected)
# while we're here, check that Series.astype behaves the same
result = Series(idx).astype(str)
expected = Series(expected, dtype="str")
tm.assert_series_equal(result, expected)

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lib/python3.11/site-packages/pandas/tests/indexes/string/test_indexing.py Normal file
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import numpy as np
import pytest
import pandas as pd
from pandas import Index
import pandas._testing as tm
def _isnan(val):
try:
return val is not pd.NA and np.isnan(val)
except TypeError:
return False
def _equivalent_na(dtype, null):
if dtype.na_value is pd.NA and null is pd.NA:
return True
elif _isnan(dtype.na_value) and _isnan(null):
return True
else:
return False
class TestGetLoc:
def test_get_loc(self, any_string_dtype):
index = Index(["a", "b", "c"], dtype=any_string_dtype)
assert index.get_loc("b") == 1
def test_get_loc_raises(self, any_string_dtype):
index = Index(["a", "b", "c"], dtype=any_string_dtype)
with pytest.raises(KeyError, match="d"):
index.get_loc("d")
def test_get_loc_invalid_value(self, any_string_dtype):
index = Index(["a", "b", "c"], dtype=any_string_dtype)
with pytest.raises(KeyError, match="1"):
index.get_loc(1)
def test_get_loc_non_unique(self, any_string_dtype):
index = Index(["a", "b", "a"], dtype=any_string_dtype)
result = index.get_loc("a")
expected = np.array([True, False, True])
tm.assert_numpy_array_equal(result, expected)
def test_get_loc_non_missing(self, any_string_dtype, nulls_fixture):
index = Index(["a", "b", "c"], dtype=any_string_dtype)
with pytest.raises(KeyError):
index.get_loc(nulls_fixture)
def test_get_loc_missing(self, any_string_dtype, nulls_fixture):
index = Index(["a", "b", nulls_fixture], dtype=any_string_dtype)
assert index.get_loc(nulls_fixture) == 2
class TestGetIndexer:
@pytest.mark.parametrize(
"method,expected",
[
("pad", [-1, 0, 1, 1]),
("backfill", [0, 0, 1, -1]),
],
)
def test_get_indexer_strings(self, any_string_dtype, method, expected):
expected = np.array(expected, dtype=np.intp)
index = Index(["b", "c"], dtype=any_string_dtype)
actual = index.get_indexer(["a", "b", "c", "d"], method=method)
tm.assert_numpy_array_equal(actual, expected)
def test_get_indexer_strings_raises(self, any_string_dtype):
index = Index(["b", "c"], dtype=any_string_dtype)
msg = "|".join(
[
"operation 'sub' not supported for dtype 'str",
r"unsupported operand type\(s\) for -: 'str' and 'str'",
]
)
with pytest.raises(TypeError, match=msg):
index.get_indexer(["a", "b", "c", "d"], method="nearest")
with pytest.raises(TypeError, match=msg):
index.get_indexer(["a", "b", "c", "d"], method="pad", tolerance=2)
with pytest.raises(TypeError, match=msg):
index.get_indexer(
["a", "b", "c", "d"], method="pad", tolerance=[2, 2, 2, 2]
)
@pytest.mark.parametrize("null", [None, np.nan, float("nan"), pd.NA])
def test_get_indexer_missing(self, any_string_dtype, null, using_infer_string):
# NaT and Decimal("NaN") from null_fixture are not supported for string dtype
index = Index(["a", "b", null], dtype=any_string_dtype)
result = index.get_indexer(["a", null, "c"])
if using_infer_string:
expected = np.array([0, 2, -1], dtype=np.intp)
elif any_string_dtype == "string" and not _equivalent_na(
any_string_dtype, null
):
expected = np.array([0, -1, -1], dtype=np.intp)
else:
expected = np.array([0, 2, -1], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
class TestGetIndexerNonUnique:
@pytest.mark.parametrize("null", [None, np.nan, float("nan"), pd.NA])
def test_get_indexer_non_unique_nas(
self, any_string_dtype, null, using_infer_string
):
index = Index(["a", "b", null], dtype=any_string_dtype)
indexer, missing = index.get_indexer_non_unique(["a", null])
if using_infer_string:
expected_indexer = np.array([0, 2], dtype=np.intp)
expected_missing = np.array([], dtype=np.intp)
elif any_string_dtype == "string" and not _equivalent_na(
any_string_dtype, null
):
expected_indexer = np.array([0, -1], dtype=np.intp)
expected_missing = np.array([1], dtype=np.intp)
else:
expected_indexer = np.array([0, 2], dtype=np.intp)
expected_missing = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected_indexer)
tm.assert_numpy_array_equal(missing, expected_missing)
# actually non-unique
index = Index(["a", null, "b", null], dtype=any_string_dtype)
indexer, missing = index.get_indexer_non_unique(["a", null])
if using_infer_string:
expected_indexer = np.array([0, 1, 3], dtype=np.intp)
elif any_string_dtype == "string" and not _equivalent_na(
any_string_dtype, null
):
pass
else:
expected_indexer = np.array([0, 1, 3], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected_indexer)
tm.assert_numpy_array_equal(missing, expected_missing)
class TestSliceLocs:
@pytest.mark.parametrize(
"in_slice,expected",
[
# error: Slice index must be an integer or None
(pd.IndexSlice[::-1], "yxdcb"),
(pd.IndexSlice["b":"y":-1], ""), # type: ignore[misc]
(pd.IndexSlice["b"::-1], "b"), # type: ignore[misc]
(pd.IndexSlice[:"b":-1], "yxdcb"), # type: ignore[misc]
(pd.IndexSlice[:"y":-1], "y"), # type: ignore[misc]
(pd.IndexSlice["y"::-1], "yxdcb"), # type: ignore[misc]
(pd.IndexSlice["y"::-4], "yb"), # type: ignore[misc]
# absent labels
(pd.IndexSlice[:"a":-1], "yxdcb"), # type: ignore[misc]
(pd.IndexSlice[:"a":-2], "ydb"), # type: ignore[misc]
(pd.IndexSlice["z"::-1], "yxdcb"), # type: ignore[misc]
(pd.IndexSlice["z"::-3], "yc"), # type: ignore[misc]
(pd.IndexSlice["m"::-1], "dcb"), # type: ignore[misc]
(pd.IndexSlice[:"m":-1], "yx"), # type: ignore[misc]
(pd.IndexSlice["a":"a":-1], ""), # type: ignore[misc]
(pd.IndexSlice["z":"z":-1], ""), # type: ignore[misc]
(pd.IndexSlice["m":"m":-1], ""), # type: ignore[misc]
],
)
def test_slice_locs_negative_step(self, in_slice, expected, any_string_dtype):
index = Index(list("bcdxy"), dtype=any_string_dtype)
s_start, s_stop = index.slice_locs(in_slice.start, in_slice.stop, in_slice.step)
result = index[s_start : s_stop : in_slice.step]
expected = Index(list(expected), dtype=any_string_dtype)
tm.assert_index_equal(result, expected)
def test_slice_locs_negative_step_oob(self, any_string_dtype):
index = Index(list("bcdxy"), dtype=any_string_dtype)
result = index[-10:5:1]
tm.assert_index_equal(result, index)
result = index[4:-10:-1]
expected = Index(list("yxdcb"), dtype=any_string_dtype)
tm.assert_index_equal(result, expected)
def test_slice_locs_dup(self, any_string_dtype):
index = Index(["a", "a", "b", "c", "d", "d"], dtype=any_string_dtype)
assert index.slice_locs("a", "d") == (0, 6)
assert index.slice_locs(end="d") == (0, 6)
assert index.slice_locs("a", "c") == (0, 4)
assert index.slice_locs("b", "d") == (2, 6)
index2 = index[::-1]
assert index2.slice_locs("d", "a") == (0, 6)
assert index2.slice_locs(end="a") == (0, 6)
assert index2.slice_locs("d", "b") == (0, 4)
assert index2.slice_locs("c", "a") == (2, 6)