202 lines
		
	
	
		
			6.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			202 lines
		
	
	
		
			6.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
from datetime import (
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    datetime,
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    timezone,
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)
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import numpy as np
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import pytest
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from pandas import (
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    CategoricalDtype,
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    CategoricalIndex,
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    DataFrame,
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    Series,
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    Timestamp,
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)
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import pandas._testing as tm
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def test_at_timezone():
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    # https://github.com/pandas-dev/pandas/issues/33544
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    result = DataFrame({"foo": [datetime(2000, 1, 1)]})
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    result.at[0, "foo"] = datetime(2000, 1, 2, tzinfo=timezone.utc)
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    expected = DataFrame(
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        {"foo": [datetime(2000, 1, 2, tzinfo=timezone.utc)]}, dtype=object
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    )
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    tm.assert_frame_equal(result, expected)
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def test_selection_methods_of_assigned_col():
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    # GH 29282
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    df = DataFrame(data={"a": [1, 2, 3], "b": [4, 5, 6]})
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    df2 = DataFrame(data={"c": [7, 8, 9]}, index=[2, 1, 0])
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    df["c"] = df2["c"]
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    df.at[1, "c"] = 11
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    result = df
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    expected = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [9, 11, 7]})
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    tm.assert_frame_equal(result, expected)
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    result = df.at[1, "c"]
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    assert result == 11
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    result = df["c"]
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    expected = Series([9, 11, 7], name="c")
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    tm.assert_series_equal(result, expected)
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    result = df[["c"]]
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    expected = DataFrame({"c": [9, 11, 7]})
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    tm.assert_frame_equal(result, expected)
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class TestAtSetItem:
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    def test_at_setitem_item_cache_cleared(self):
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        # GH#22372 Note the multi-step construction is necessary to trigger
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        #  the original bug. pandas/issues/22372#issuecomment-413345309
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        df = DataFrame(index=[0])
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        df["x"] = 1
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        df["cost"] = 2
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        # accessing df["cost"] adds "cost" to the _item_cache
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        df["cost"]
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        # This loc[[0]] lookup used to call _consolidate_inplace at the
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        #  BlockManager level, which failed to clear the _item_cache
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        df.loc[[0]]
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        df.at[0, "x"] = 4
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        df.at[0, "cost"] = 789
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        expected = DataFrame({"x": [4], "cost": 789}, index=[0])
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        tm.assert_frame_equal(df, expected)
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        # And in particular, check that the _item_cache has updated correctly.
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        tm.assert_series_equal(df["cost"], expected["cost"])
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    def test_at_setitem_mixed_index_assignment(self):
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        # GH#19860
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        ser = Series([1, 2, 3, 4, 5], index=["a", "b", "c", 1, 2])
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        ser.at["a"] = 11
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        assert ser.iat[0] == 11
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        ser.at[1] = 22
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        assert ser.iat[3] == 22
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    def test_at_setitem_categorical_missing(self):
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        df = DataFrame(
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            index=range(3), columns=range(3), dtype=CategoricalDtype(["foo", "bar"])
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        )
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        df.at[1, 1] = "foo"
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        expected = DataFrame(
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            [
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                [np.nan, np.nan, np.nan],
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                [np.nan, "foo", np.nan],
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                [np.nan, np.nan, np.nan],
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            ],
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            dtype=CategoricalDtype(["foo", "bar"]),
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        )
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        tm.assert_frame_equal(df, expected)
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class TestAtSetItemWithExpansion:
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    def test_at_setitem_expansion_series_dt64tz_value(self, tz_naive_fixture):
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        # GH#25506
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        ts = Timestamp("2017-08-05 00:00:00+0100", tz=tz_naive_fixture)
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        result = Series(ts)
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        result.at[1] = ts
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        expected = Series([ts, ts])
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        tm.assert_series_equal(result, expected)
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class TestAtWithDuplicates:
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    def test_at_with_duplicate_axes_requires_scalar_lookup(self):
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        # GH#33041 check that falling back to loc doesn't allow non-scalar
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        #  args to slip in
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        arr = np.random.randn(6).reshape(3, 2)
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        df = DataFrame(arr, columns=["A", "A"])
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        msg = "Invalid call for scalar access"
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        with pytest.raises(ValueError, match=msg):
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            df.at[[1, 2]]
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        with pytest.raises(ValueError, match=msg):
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            df.at[1, ["A"]]
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        with pytest.raises(ValueError, match=msg):
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            df.at[:, "A"]
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        with pytest.raises(ValueError, match=msg):
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            df.at[[1, 2]] = 1
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        with pytest.raises(ValueError, match=msg):
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            df.at[1, ["A"]] = 1
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        with pytest.raises(ValueError, match=msg):
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            df.at[:, "A"] = 1
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class TestAtErrors:
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    # TODO: De-duplicate/parametrize
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    #  test_at_series_raises_key_error2, test_at_frame_raises_key_error2
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    def test_at_series_raises_key_error(self, indexer_al):
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        # GH#31724 .at should match .loc
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        ser = Series([1, 2, 3], index=[3, 2, 1])
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        result = indexer_al(ser)[1]
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        assert result == 3
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        with pytest.raises(KeyError, match="a"):
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            indexer_al(ser)["a"]
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    def test_at_frame_raises_key_error(self, indexer_al):
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        # GH#31724 .at should match .loc
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        df = DataFrame({0: [1, 2, 3]}, index=[3, 2, 1])
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        result = indexer_al(df)[1, 0]
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        assert result == 3
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        with pytest.raises(KeyError, match="a"):
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            indexer_al(df)["a", 0]
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        with pytest.raises(KeyError, match="a"):
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            indexer_al(df)[1, "a"]
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    def test_at_series_raises_key_error2(self, indexer_al):
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        # at should not fallback
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        # GH#7814
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        # GH#31724 .at should match .loc
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        ser = Series([1, 2, 3], index=list("abc"))
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        result = indexer_al(ser)["a"]
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        assert result == 1
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        with pytest.raises(KeyError, match="^0$"):
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            indexer_al(ser)[0]
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    def test_at_frame_raises_key_error2(self, indexer_al):
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        # GH#31724 .at should match .loc
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        df = DataFrame({"A": [1, 2, 3]}, index=list("abc"))
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        result = indexer_al(df)["a", "A"]
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        assert result == 1
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        with pytest.raises(KeyError, match="^0$"):
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            indexer_al(df)["a", 0]
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    def test_at_getitem_mixed_index_no_fallback(self):
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        # GH#19860
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        ser = Series([1, 2, 3, 4, 5], index=["a", "b", "c", 1, 2])
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        with pytest.raises(KeyError, match="^0$"):
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            ser.at[0]
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        with pytest.raises(KeyError, match="^4$"):
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            ser.at[4]
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    def test_at_categorical_integers(self):
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        # CategoricalIndex with integer categories that don't happen to match
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        #  the Categorical's codes
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        ci = CategoricalIndex([3, 4])
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        arr = np.arange(4).reshape(2, 2)
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        frame = DataFrame(arr, index=ci)
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        for df in [frame, frame.T]:
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            for key in [0, 1]:
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                with pytest.raises(KeyError, match=str(key)):
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                    df.at[key, key]
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