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| import operator
| import re
|
| import numpy as np
| import pytest
|
| from pandas import (
| CategoricalIndex,
| DataFrame,
| Interval,
| Series,
| isnull,
| )
| import pandas._testing as tm
|
|
| class TestDataFrameLogicalOperators:
| # &, |, ^
|
| @pytest.mark.parametrize(
| "left, right, op, expected",
| [
| (
| [True, False, np.nan],
| [True, False, True],
| operator.and_,
| [True, False, False],
| ),
| (
| [True, False, True],
| [True, False, np.nan],
| operator.and_,
| [True, False, False],
| ),
| (
| [True, False, np.nan],
| [True, False, True],
| operator.or_,
| [True, False, False],
| ),
| (
| [True, False, True],
| [True, False, np.nan],
| operator.or_,
| [True, False, True],
| ),
| ],
| )
| def test_logical_operators_nans(self, left, right, op, expected, frame_or_series):
| # GH#13896
| result = op(frame_or_series(left), frame_or_series(right))
| expected = frame_or_series(expected)
|
| tm.assert_equal(result, expected)
|
| def test_logical_ops_empty_frame(self):
| # GH#5808
| # empty frames, non-mixed dtype
| df = DataFrame(index=[1])
|
| result = df & df
| tm.assert_frame_equal(result, df)
|
| result = df | df
| tm.assert_frame_equal(result, df)
|
| df2 = DataFrame(index=[1, 2])
| result = df & df2
| tm.assert_frame_equal(result, df2)
|
| dfa = DataFrame(index=[1], columns=["A"])
|
| result = dfa & dfa
| expected = DataFrame(False, index=[1], columns=["A"])
| tm.assert_frame_equal(result, expected)
|
| def test_logical_ops_bool_frame(self):
| # GH#5808
| df1a_bool = DataFrame(True, index=[1], columns=["A"])
|
| result = df1a_bool & df1a_bool
| tm.assert_frame_equal(result, df1a_bool)
|
| result = df1a_bool | df1a_bool
| tm.assert_frame_equal(result, df1a_bool)
|
| def test_logical_ops_int_frame(self):
| # GH#5808
| df1a_int = DataFrame(1, index=[1], columns=["A"])
| df1a_bool = DataFrame(True, index=[1], columns=["A"])
|
| result = df1a_int | df1a_bool
| tm.assert_frame_equal(result, df1a_bool)
|
| # Check that this matches Series behavior
| res_ser = df1a_int["A"] | df1a_bool["A"]
| tm.assert_series_equal(res_ser, df1a_bool["A"])
|
| def test_logical_ops_invalid(self):
| # GH#5808
|
| df1 = DataFrame(1.0, index=[1], columns=["A"])
| df2 = DataFrame(True, index=[1], columns=["A"])
| msg = re.escape("unsupported operand type(s) for |: 'float' and 'bool'")
| with pytest.raises(TypeError, match=msg):
| df1 | df2
|
| df1 = DataFrame("foo", index=[1], columns=["A"])
| df2 = DataFrame(True, index=[1], columns=["A"])
| msg = re.escape("unsupported operand type(s) for |: 'str' and 'bool'")
| with pytest.raises(TypeError, match=msg):
| df1 | df2
|
| def test_logical_operators(self):
| def _check_bin_op(op):
| result = op(df1, df2)
| expected = DataFrame(
| op(df1.values, df2.values), index=df1.index, columns=df1.columns
| )
| assert result.values.dtype == np.bool_
| tm.assert_frame_equal(result, expected)
|
| def _check_unary_op(op):
| result = op(df1)
| expected = DataFrame(op(df1.values), index=df1.index, columns=df1.columns)
| assert result.values.dtype == np.bool_
| tm.assert_frame_equal(result, expected)
|
| df1 = {
| "a": {"a": True, "b": False, "c": False, "d": True, "e": True},
| "b": {"a": False, "b": True, "c": False, "d": False, "e": False},
| "c": {"a": False, "b": False, "c": True, "d": False, "e": False},
| "d": {"a": True, "b": False, "c": False, "d": True, "e": True},
| "e": {"a": True, "b": False, "c": False, "d": True, "e": True},
| }
|
| df2 = {
| "a": {"a": True, "b": False, "c": True, "d": False, "e": False},
| "b": {"a": False, "b": True, "c": False, "d": False, "e": False},
| "c": {"a": True, "b": False, "c": True, "d": False, "e": False},
| "d": {"a": False, "b": False, "c": False, "d": True, "e": False},
| "e": {"a": False, "b": False, "c": False, "d": False, "e": True},
| }
|
| df1 = DataFrame(df1)
| df2 = DataFrame(df2)
|
| _check_bin_op(operator.and_)
| _check_bin_op(operator.or_)
| _check_bin_op(operator.xor)
|
| _check_unary_op(operator.inv) # TODO: belongs elsewhere
|
| def test_logical_with_nas(self):
| d = DataFrame({"a": [np.nan, False], "b": [True, True]})
|
| # GH4947
| # bool comparisons should return bool
| result = d["a"] | d["b"]
| expected = Series([False, True])
| tm.assert_series_equal(result, expected)
|
| # GH4604, automatic casting here
| result = d["a"].fillna(False) | d["b"]
| expected = Series([True, True])
| tm.assert_series_equal(result, expected)
|
| result = d["a"].fillna(False, downcast=False) | d["b"]
| expected = Series([True, True])
| tm.assert_series_equal(result, expected)
|
| def test_logical_ops_categorical_columns(self):
| # GH#38367
| intervals = [Interval(1, 2), Interval(3, 4)]
| data = DataFrame(
| [[1, np.nan], [2, np.nan]],
| columns=CategoricalIndex(
| intervals, categories=intervals + [Interval(5, 6)]
| ),
| )
| mask = DataFrame(
| [[False, False], [False, False]], columns=data.columns, dtype=bool
| )
| result = mask | isnull(data)
| expected = DataFrame(
| [[False, True], [False, True]],
| columns=CategoricalIndex(
| intervals, categories=intervals + [Interval(5, 6)]
| ),
| )
| tm.assert_frame_equal(result, expected)
|
|
