FM / boolean

/usr/local/lib64/python3.6/site-packages/pandas/tests/arrays/boolean/

/usr/local/lib64/python3.6/site-packages/pandas/tests/arrays/boolean

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
test_arithmetic.py	2704	0644	edit dl rm
test_astype.py	1603	0644	edit dl rm
test_comparison.py	3103	0644	edit dl rm
test_construction.py	13025	0644	edit dl rm
test_function.py	3441	0644	edit dl rm
test_indexing.py	361	0644	edit dl rm
test_logical.py	8501	0644	edit dl rm
test_ops.py	745	0644	edit dl rm
test_reduction.py	2017	0644	edit dl rm
test_repr.py	437	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/arrays/boolean/test_comparison.py (3103B)

import numpy as np
import pytest

import pandas as pd
import pandas._testing as tm
from pandas.arrays import BooleanArray
from pandas.tests.extension.base import BaseOpsUtil

@pytest.fixture
def data():
    return pd.array(
        [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
        dtype="boolean",
    )

class TestComparisonOps(BaseOpsUtil):
    def _compare_other(self, data, op_name, other):
        op = self.get_op_from_name(op_name)

# array
        result = pd.Series(op(data, other))
        expected = pd.Series(op(data._data, other), dtype="boolean")
        # propagate NAs
        expected[data._mask] = pd.NA

tm.assert_series_equal(result, expected)

# series
        s = pd.Series(data)
        result = op(s, other)

expected = pd.Series(data._data)
        expected = op(expected, other)
        expected = expected.astype("boolean")
        # propagate NAs
        expected[data._mask] = pd.NA

tm.assert_series_equal(result, expected)

def test_compare_scalar(self, data, all_compare_operators):
        op_name = all_compare_operators
        self._compare_other(data, op_name, True)

def test_compare_array(self, data, all_compare_operators):
        op_name = all_compare_operators
        other = pd.array([True] * len(data), dtype="boolean")
        self._compare_other(data, op_name, other)
        other = np.array([True] * len(data))
        self._compare_other(data, op_name, other)
        other = pd.Series([True] * len(data))
        self._compare_other(data, op_name, other)

@pytest.mark.parametrize("other", [True, False, pd.NA])
    def test_scalar(self, other, all_compare_operators):
        op = self.get_op_from_name(all_compare_operators)
        a = pd.array([True, False, None], dtype="boolean")

result = op(a, other)

if other is pd.NA:
            expected = pd.array([None, None, None], dtype="boolean")
        else:
            values = op(a._data, other)
            expected = BooleanArray(values, a._mask, copy=True)
        tm.assert_extension_array_equal(result, expected)

# ensure we haven't mutated anything inplace
        result[0] = None
        tm.assert_extension_array_equal(
            a, pd.array([True, False, None], dtype="boolean")
        )

def test_array(self, all_compare_operators):
        op = self.get_op_from_name(all_compare_operators)
        a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
        b = pd.array([True, False, None] * 3, dtype="boolean")

result = op(a, b)

values = op(a._data, b._data)
        mask = a._mask | b._mask
        expected = BooleanArray(values, mask)
        tm.assert_extension_array_equal(result, expected)

# ensure we haven't mutated anything inplace
        result[0] = None
        tm.assert_extension_array_equal(
            a, pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
        )
        tm.assert_extension_array_equal(
            b, pd.array([True, False, None] * 3, dtype="boolean")
        )

import numpy as np import pytest import pandas as pd import pandas._testing as tm from pandas.arrays import BooleanArray from pandas.tests.extension.base import BaseOpsUtil @pytest.fixture def data(): return pd.array( [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False], dtype="boolean", ) class TestComparisonOps(BaseOpsUtil): def _compare_other(self, data, op_name, other): op = self.get_op_from_name(op_name) # array result = pd.Series(op(data, other)) expected = pd.Series(op(data._data, other), dtype="boolean") # propagate NAs expected[data._mask] = pd.NA tm.assert_series_equal(result, expected) # series s = pd.Series(data) result = op(s, other) expected = pd.Series(data._data) expected = op(expected, other) expected = expected.astype("boolean") # propagate NAs expected[data._mask] = pd.NA tm.assert_series_equal(result, expected) def test_compare_scalar(self, data, all_compare_operators): op_name = all_compare_operators self._compare_other(data, op_name, True) def test_compare_array(self, data, all_compare_operators): op_name = all_compare_operators other = pd.array([True] * len(data), dtype="boolean") self._compare_other(data, op_name, other) other = np.array([True] * len(data)) self._compare_other(data, op_name, other) other = pd.Series([True] * len(data)) self._compare_other(data, op_name, other) @pytest.mark.parametrize("other", [True, False, pd.NA]) def test_scalar(self, other, all_compare_operators): op = self.get_op_from_name(all_compare_operators) a = pd.array([True, False, None], dtype="boolean") result = op(a, other) if other is pd.NA: expected = pd.array([None, None, None], dtype="boolean") else: values = op(a._data, other) expected = BooleanArray(values, a._mask, copy=True) tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace result[0] = None tm.assert_extension_array_equal( a, pd.array([True, False, None], dtype="boolean") ) def test_array(self, all_compare_operators): op = self.get_op_from_name(all_compare_operators) a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") b = pd.array([True, False, None] * 3, dtype="boolean") result = op(a, b) values = op(a._data, b._data) mask = a._mask | b._mask expected = BooleanArray(values, mask) tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace result[0] = None tm.assert_extension_array_equal( a, pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") ) tm.assert_extension_array_equal( b, pd.array([True, False, None] * 3, dtype="boolean") )