from datetime import datetime, timezone import numpy as np import pytest from pandas import CategoricalDtype, DataFrame, Series, Timestamp import pandas._testing as tm def test_at_timezone(): # https://github.com/pandas-dev/pandas/issues/33544 result = DataFrame({"foo": [datetime(2000, 1, 1)]}) result.at[0, "foo"] = datetime(2000, 1, 2, tzinfo=timezone.utc) expected = DataFrame( {"foo": [datetime(2000, 1, 2, tzinfo=timezone.utc)]}, dtype=object ) tm.assert_frame_equal(result, expected) class TestAtSetItem: def test_at_setitem_mixed_index_assignment(self): # GH#19860 ser = Series([1, 2, 3, 4, 5], index=["a", "b", "c", 1, 2]) ser.at["a"] = 11 assert ser.iat[0] == 11 ser.at[1] = 22 assert ser.iat[3] == 22 def test_at_setitem_categorical_missing(self): df = DataFrame( index=range(3), columns=range(3), dtype=CategoricalDtype(["foo", "bar"]) ) df.at[1, 1] = "foo" expected = DataFrame( [ [np.nan, np.nan, np.nan], [np.nan, "foo", np.nan], [np.nan, np.nan, np.nan], ], dtype=CategoricalDtype(["foo", "bar"]), ) tm.assert_frame_equal(df, expected) class TestAtSetItemWithExpansion: def test_at_setitem_expansion_series_dt64tz_value(self, tz_naive_fixture): # GH#25506 ts = Timestamp("2017-08-05 00:00:00+0100", tz=tz_naive_fixture) result = Series(ts) result.at[1] = ts expected = Series([ts, ts]) tm.assert_series_equal(result, expected) class TestAtWithDuplicates: def test_at_with_duplicate_axes_requires_scalar_lookup(self): # GH#33041 check that falling back to loc doesn't allow non-scalar # args to slip in arr = np.random.randn(6).reshape(3, 2) df = DataFrame(arr, columns=["A", "A"]) msg = "Invalid call for scalar access" with pytest.raises(ValueError, match=msg): df.at[[1, 2]] with pytest.raises(ValueError, match=msg): df.at[1, ["A"]] with pytest.raises(ValueError, match=msg): df.at[:, "A"] with pytest.raises(ValueError, match=msg): df.at[[1, 2]] = 1 with pytest.raises(ValueError, match=msg): df.at[1, ["A"]] = 1 with pytest.raises(ValueError, match=msg): df.at[:, "A"] = 1 class TestAtErrors: # TODO: De-duplicate/parametrize # test_at_series_raises_key_error, test_at_frame_raises_key_error, # test_at_series_raises_key_error2, test_at_frame_raises_key_error2 def test_at_series_raises_key_error(self): # GH#31724 .at should match .loc ser = Series([1, 2, 3], index=[3, 2, 1]) result = ser.at[1] assert result == 3 result = ser.loc[1] assert result == 3 with pytest.raises(KeyError, match="a"): ser.at["a"] with pytest.raises(KeyError, match="a"): # .at should match .loc ser.loc["a"] def test_at_frame_raises_key_error(self): # GH#31724 .at should match .loc df = DataFrame({0: [1, 2, 3]}, index=[3, 2, 1]) result = df.at[1, 0] assert result == 3 result = df.loc[1, 0] assert result == 3 with pytest.raises(KeyError, match="a"): df.at["a", 0] with pytest.raises(KeyError, match="a"): df.loc["a", 0] with pytest.raises(KeyError, match="a"): df.at[1, "a"] with pytest.raises(KeyError, match="a"): df.loc[1, "a"] def test_at_series_raises_key_error2(self): # at should not fallback # GH#7814 # GH#31724 .at should match .loc ser = Series([1, 2, 3], index=list("abc")) result = ser.at["a"] assert result == 1 result = ser.loc["a"] assert result == 1 with pytest.raises(KeyError, match="^0$"): ser.at[0] with pytest.raises(KeyError, match="^0$"): ser.loc[0] def test_at_frame_raises_key_error2(self): # GH#31724 .at should match .loc df = DataFrame({"A": [1, 2, 3]}, index=list("abc")) result = df.at["a", "A"] assert result == 1 result = df.loc["a", "A"] assert result == 1 with pytest.raises(KeyError, match="^0$"): df.at["a", 0] with pytest.raises(KeyError, match="^0$"): df.loc["a", 0] def test_at_getitem_mixed_index_no_fallback(self): # GH#19860 ser = Series([1, 2, 3, 4, 5], index=["a", "b", "c", 1, 2]) with pytest.raises(KeyError, match="^0$"): ser.at[0] with pytest.raises(KeyError, match="^4$"): ser.at[4]