A PyQT GUI application for converting InfoLease report outputs into Excel files. Handles parsing and summarizing. Learns where files are meant to be store and compiles monthly and yearly summaries.
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InfoLeaseExtract/venv/Lib/site-packages/pandas/tests/arrays/boolean/test_comparison.py

58 lines
1.8 KiB

import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.arrays import BooleanArray
from pandas.tests.arrays.masked_shared import ComparisonOps
@pytest.fixture
def data():
return pd.array(
[True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
dtype="boolean",
)
@pytest.fixture
def dtype():
return pd.BooleanDtype()
class TestComparisonOps(ComparisonOps):
def test_compare_scalar(self, data, comparison_op):
self._compare_other(data, comparison_op, True)
def test_compare_array(self, data, comparison_op):
other = pd.array([True] * len(data), dtype="boolean")
self._compare_other(data, comparison_op, other)
other = np.array([True] * len(data))
self._compare_other(data, comparison_op, other)
other = pd.Series([True] * len(data))
self._compare_other(data, comparison_op, other)
@pytest.mark.parametrize("other", [True, False, pd.NA])
def test_scalar(self, other, comparison_op, dtype):
ComparisonOps.test_scalar(self, other, comparison_op, dtype)
def test_array(self, comparison_op):
op = comparison_op
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")
)