Current File : //backups/router/usr/local/lib/python3.11/site-packages/pandas/tests/extension/test_categorical.py
"""
This file contains a minimal set of tests for compliance with the extension
array interface test suite, and should contain no other tests.
The test suite for the full functionality of the array is located in
`pandas/tests/arrays/`.
The tests in this file are inherited from the BaseExtensionTests, and only
minimal tweaks should be applied to get the tests passing (by overwriting a
parent method).
Additional tests should either be added to one of the BaseExtensionTests
classes (if they are relevant for the extension interface for all dtypes), or
be added to the array-specific tests in `pandas/tests/arrays/`.
"""
import string
import numpy as np
import pytest
import pandas as pd
from pandas import Categorical
import pandas._testing as tm
from pandas.api.types import CategoricalDtype
from pandas.tests.extension import base
def make_data():
while True:
values = np.random.default_rng(2).choice(list(string.ascii_letters), size=100)
# ensure we meet the requirements
# 1. first two not null
# 2. first and second are different
if values[0] != values[1]:
break
return values
@pytest.fixture
def dtype():
return CategoricalDtype()
@pytest.fixture
def data():
"""Length-100 array for this type.
* data[0] and data[1] should both be non missing
* data[0] and data[1] should not be equal
"""
return Categorical(make_data())
@pytest.fixture
def data_missing():
"""Length 2 array with [NA, Valid]"""
return Categorical([np.nan, "A"])
@pytest.fixture
def data_for_sorting():
return Categorical(["A", "B", "C"], categories=["C", "A", "B"], ordered=True)
@pytest.fixture
def data_missing_for_sorting():
return Categorical(["A", None, "B"], categories=["B", "A"], ordered=True)
@pytest.fixture
def data_for_grouping():
return Categorical(["a", "a", None, None, "b", "b", "a", "c"])
class TestDtype(base.BaseDtypeTests):
pass
class TestInterface(base.BaseInterfaceTests):
@pytest.mark.xfail(reason="Memory usage doesn't match")
def test_memory_usage(self, data):
# TODO: Is this deliberate?
super().test_memory_usage(data)
def test_contains(self, data, data_missing):
# GH-37867
# na value handling in Categorical.__contains__ is deprecated.
# See base.BaseInterFaceTests.test_contains for more details.
na_value = data.dtype.na_value
# ensure data without missing values
data = data[~data.isna()]
# first elements are non-missing
assert data[0] in data
assert data_missing[0] in data_missing
# check the presence of na_value
assert na_value in data_missing
assert na_value not in data
# Categoricals can contain other nan-likes than na_value
for na_value_obj in tm.NULL_OBJECTS:
if na_value_obj is na_value:
continue
assert na_value_obj not in data
assert na_value_obj in data_missing # this line differs from super method
class TestConstructors(base.BaseConstructorsTests):
def test_empty(self, dtype):
cls = dtype.construct_array_type()
result = cls._empty((4,), dtype=dtype)
assert isinstance(result, cls)
# the dtype we passed is not initialized, so will not match the
# dtype on our result.
assert result.dtype == CategoricalDtype([])
class TestReshaping(base.BaseReshapingTests):
pass
class TestGetitem(base.BaseGetitemTests):
@pytest.mark.skip(reason="Backwards compatibility")
def test_getitem_scalar(self, data):
# CategoricalDtype.type isn't "correct" since it should
# be a parent of the elements (object). But don't want
# to break things by changing.
super().test_getitem_scalar(data)
class TestSetitem(base.BaseSetitemTests):
pass
class TestIndex(base.BaseIndexTests):
pass
class TestMissing(base.BaseMissingTests):
pass
class TestReduce(base.BaseReduceTests):
pass
class TestAccumulate(base.BaseAccumulateTests):
pass
class TestMethods(base.BaseMethodsTests):
@pytest.mark.xfail(reason="Unobserved categories included")
def test_value_counts(self, all_data, dropna):
return super().test_value_counts(all_data, dropna)
def test_combine_add(self, data_repeated):
# GH 20825
# When adding categoricals in combine, result is a string
orig_data1, orig_data2 = data_repeated(2)
s1 = pd.Series(orig_data1)
s2 = pd.Series(orig_data2)
result = s1.combine(s2, lambda x1, x2: x1 + x2)
expected = pd.Series(
[a + b for (a, b) in zip(list(orig_data1), list(orig_data2))]
)
tm.assert_series_equal(result, expected)
val = s1.iloc[0]
result = s1.combine(val, lambda x1, x2: x1 + x2)
expected = pd.Series([a + val for a in list(orig_data1)])
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize("na_action", [None, "ignore"])
def test_map(self, data, na_action):
result = data.map(lambda x: x, na_action=na_action)
tm.assert_extension_array_equal(result, data)
class TestCasting(base.BaseCastingTests):
pass
class TestArithmeticOps(base.BaseArithmeticOpsTests):
def test_arith_frame_with_scalar(self, data, all_arithmetic_operators, request):
# frame & scalar
op_name = all_arithmetic_operators
if op_name == "__rmod__":
request.node.add_marker(
pytest.mark.xfail(
reason="rmod never called when string is first argument"
)
)
super().test_arith_frame_with_scalar(data, op_name)
def test_arith_series_with_scalar(self, data, all_arithmetic_operators, request):
op_name = all_arithmetic_operators
if op_name == "__rmod__":
request.node.add_marker(
pytest.mark.xfail(
reason="rmod never called when string is first argument"
)
)
super().test_arith_series_with_scalar(data, op_name)
class TestComparisonOps(base.BaseComparisonOpsTests):
def _compare_other(self, s, data, op, other):
op_name = f"__{op.__name__}__"
if op_name not in ["__eq__", "__ne__"]:
msg = "Unordered Categoricals can only compare equality or not"
with pytest.raises(TypeError, match=msg):
op(data, other)
else:
return super()._compare_other(s, data, op, other)
class TestParsing(base.BaseParsingTests):
pass
class Test2DCompat(base.NDArrayBacked2DTests):
def test_repr_2d(self, data):
# Categorical __repr__ doesn't include "Categorical", so we need
# to special-case
res = repr(data.reshape(1, -1))
assert res.count("\nCategories") == 1
res = repr(data.reshape(-1, 1))
assert res.count("\nCategories") == 1
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