324 lines
10 KiB
Python
324 lines
10 KiB
Python
import pytest
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import pandas as pd
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from pandas import DataFrame
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import pandas._testing as tm
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@pytest.fixture(params=[True, False])
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def by_blocks_fixture(request):
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return request.param
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@pytest.fixture(params=["DataFrame", "Series"])
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def obj_fixture(request):
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return request.param
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def _assert_frame_equal_both(a, b, **kwargs):
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"""
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Check that two DataFrame equal.
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This check is performed commutatively.
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Parameters
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----------
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a : DataFrame
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The first DataFrame to compare.
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b : DataFrame
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The second DataFrame to compare.
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kwargs : dict
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The arguments passed to `tm.assert_frame_equal`.
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"""
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tm.assert_frame_equal(a, b, **kwargs)
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tm.assert_frame_equal(b, a, **kwargs)
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def _assert_not_frame_equal(a, b, **kwargs):
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"""
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Check that two DataFrame are not equal.
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Parameters
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----------
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a : DataFrame
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The first DataFrame to compare.
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b : DataFrame
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The second DataFrame to compare.
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kwargs : dict
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The arguments passed to `tm.assert_frame_equal`.
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"""
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msg = "The two DataFrames were equal when they shouldn't have been"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(a, b, **kwargs)
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def _assert_not_frame_equal_both(a, b, **kwargs):
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"""
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Check that two DataFrame are not equal.
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This check is performed commutatively.
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Parameters
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----------
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a : DataFrame
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The first DataFrame to compare.
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b : DataFrame
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The second DataFrame to compare.
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kwargs : dict
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The arguments passed to `tm.assert_frame_equal`.
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"""
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_assert_not_frame_equal(a, b, **kwargs)
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_assert_not_frame_equal(b, a, **kwargs)
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@pytest.mark.parametrize("check_like", [True, False])
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def test_frame_equal_row_order_mismatch(check_like, obj_fixture):
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df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
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df2 = DataFrame({"A": [3, 2, 1], "B": [6, 5, 4]}, index=["c", "b", "a"])
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if not check_like: # Do not ignore row-column orderings.
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msg = f"{obj_fixture}.index are different"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
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else:
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_assert_frame_equal_both(df1, df2, check_like=check_like, obj=obj_fixture)
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@pytest.mark.parametrize(
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"df1,df2",
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[
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(DataFrame({"A": [1, 2, 3]}), DataFrame({"A": [1, 2, 3, 4]})),
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(DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), DataFrame({"A": [1, 2, 3]})),
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],
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)
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def test_frame_equal_shape_mismatch(df1, df2, obj_fixture):
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msg = f"{obj_fixture} are different"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, obj=obj_fixture)
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@pytest.mark.parametrize(
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"df1,df2,msg",
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[
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# Index
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(
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DataFrame.from_records({"a": [1, 2], "c": ["l1", "l2"]}, index=["a"]),
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DataFrame.from_records({"a": [1.0, 2.0], "c": ["l1", "l2"]}, index=["a"]),
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"DataFrame\\.index are different",
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),
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# MultiIndex
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(
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DataFrame.from_records(
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{"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
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),
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DataFrame.from_records(
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{"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
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),
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"MultiIndex level \\[0\\] are different",
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),
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],
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)
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def test_frame_equal_index_dtype_mismatch(df1, df2, msg, check_index_type):
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kwargs = {"check_index_type": check_index_type}
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if check_index_type:
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, **kwargs)
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else:
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tm.assert_frame_equal(df1, df2, **kwargs)
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def test_empty_dtypes(check_dtype):
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columns = ["col1", "col2"]
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df1 = DataFrame(columns=columns)
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df2 = DataFrame(columns=columns)
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kwargs = {"check_dtype": check_dtype}
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df1["col1"] = df1["col1"].astype("int64")
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if check_dtype:
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msg = r"Attributes of DataFrame\..* are different"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, **kwargs)
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else:
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tm.assert_frame_equal(df1, df2, **kwargs)
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@pytest.mark.parametrize("check_like", [True, False])
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def test_frame_equal_index_mismatch(check_like, obj_fixture):
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msg = f"""{obj_fixture}\\.index are different
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{obj_fixture}\\.index values are different \\(33\\.33333 %\\)
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\\[left\\]: Index\\(\\['a', 'b', 'c'\\], dtype='object'\\)
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\\[right\\]: Index\\(\\['a', 'b', 'd'\\], dtype='object'\\)"""
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df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
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df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "d"])
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
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@pytest.mark.parametrize("check_like", [True, False])
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def test_frame_equal_columns_mismatch(check_like, obj_fixture):
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msg = f"""{obj_fixture}\\.columns are different
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{obj_fixture}\\.columns values are different \\(50\\.0 %\\)
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\\[left\\]: Index\\(\\['A', 'B'\\], dtype='object'\\)
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\\[right\\]: Index\\(\\['A', 'b'\\], dtype='object'\\)"""
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df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
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df2 = DataFrame({"A": [1, 2, 3], "b": [4, 5, 6]}, index=["a", "b", "c"])
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
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def test_frame_equal_block_mismatch(by_blocks_fixture, obj_fixture):
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obj = obj_fixture
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msg = f"""{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) are different
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{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) values are different \\(33\\.33333 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\[4, 5, 6\\]
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\\[right\\]: \\[4, 5, 7\\]"""
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df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
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df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 7]})
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture)
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@pytest.mark.parametrize(
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"df1,df2,msg",
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[
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(
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DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}),
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DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "e̊"]}),
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"""{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) are different
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{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) values are different \\(33\\.33333 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\[é, è, ë\\]
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\\[right\\]: \\[é, è, e̊\\]""",
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),
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(
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DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}),
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DataFrame({"A": ["a", "a", "a"], "E": ["e", "e", "e"]}),
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"""{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) are different
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{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) values are different \\(100\\.0 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\[á, à, ä\\]
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\\[right\\]: \\[a, a, a\\]""",
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),
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],
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)
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def test_frame_equal_unicode(df1, df2, msg, by_blocks_fixture, obj_fixture):
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# see gh-20503
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#
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# Test ensures that `tm.assert_frame_equals` raises the right exception
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# when comparing DataFrames containing differing unicode objects.
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msg = msg.format(obj=obj_fixture)
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture)
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def test_assert_frame_equal_extension_dtype_mismatch():
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# https://github.com/pandas-dev/pandas/issues/32747
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left = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
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right = left.astype(int)
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msg = (
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"Attributes of DataFrame\\.iloc\\[:, 0\\] "
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'\\(column name="a"\\) are different\n\n'
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'Attribute "dtype" are different\n'
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"\\[left\\]: Int64\n"
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"\\[right\\]: int[32|64]"
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)
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tm.assert_frame_equal(left, right, check_dtype=False)
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(left, right, check_dtype=True)
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def test_assert_frame_equal_interval_dtype_mismatch():
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# https://github.com/pandas-dev/pandas/issues/32747
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left = DataFrame({"a": [pd.Interval(0, 1)]}, dtype="interval")
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right = left.astype(object)
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msg = (
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"Attributes of DataFrame\\.iloc\\[:, 0\\] "
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'\\(column name="a"\\) are different\n\n'
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'Attribute "dtype" are different\n'
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"\\[left\\]: interval\\[int64\\]\n"
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"\\[right\\]: object"
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)
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tm.assert_frame_equal(left, right, check_dtype=False)
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with pytest.raises(AssertionError, match=msg):
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tm.assert_frame_equal(left, right, check_dtype=True)
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@pytest.mark.parametrize("right_dtype", ["Int32", "int64"])
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def test_assert_frame_equal_ignore_extension_dtype_mismatch(right_dtype):
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# https://github.com/pandas-dev/pandas/issues/35715
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left = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
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right = DataFrame({"a": [1, 2, 3]}, dtype=right_dtype)
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tm.assert_frame_equal(left, right, check_dtype=False)
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@pytest.mark.parametrize(
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"dtype",
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[
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("timedelta64[ns]"),
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("datetime64[ns, UTC]"),
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("Period[D]"),
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],
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)
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def test_assert_frame_equal_datetime_like_dtype_mismatch(dtype):
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df1 = DataFrame({"a": []}, dtype=dtype)
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df2 = DataFrame({"a": []})
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tm.assert_frame_equal(df1, df2, check_dtype=False)
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def test_allows_duplicate_labels():
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left = DataFrame()
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right = DataFrame().set_flags(allows_duplicate_labels=False)
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tm.assert_frame_equal(left, left)
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tm.assert_frame_equal(right, right)
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tm.assert_frame_equal(left, right, check_flags=False)
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tm.assert_frame_equal(right, left, check_flags=False)
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with pytest.raises(AssertionError, match="<Flags"):
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tm.assert_frame_equal(left, right)
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with pytest.raises(AssertionError, match="<Flags"):
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tm.assert_frame_equal(left, right)
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def test_assert_frame_equal_columns_mixed_dtype():
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# GH#39168
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df = DataFrame([[0, 1, 2]], columns=["foo", "bar", 42], index=[1, "test", 2])
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tm.assert_frame_equal(df, df, check_like=True)
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def test_frame_equal_extension_dtype(frame_or_series, any_numeric_dtype):
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# GH#39410
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obj = frame_or_series([1, 2], dtype=any_numeric_dtype)
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tm.assert_equal(obj, obj, check_exact=True)
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@pytest.mark.parametrize("indexer", [(0, 1), (1, 0)])
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def test_frame_equal_mixed_dtypes(frame_or_series, any_numeric_dtype, indexer):
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dtypes = (any_numeric_dtype, "int64")
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obj1 = frame_or_series([1, 2], dtype=dtypes[indexer[0]])
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obj2 = frame_or_series([1, 2], dtype=dtypes[indexer[1]])
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msg = r'(Series|DataFrame.iloc\[:, 0\] \(column name="0"\) classes) are different'
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with pytest.raises(AssertionError, match=msg):
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tm.assert_equal(obj1, obj2, check_exact=True, check_dtype=False)
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