251 lines
6.4 KiB
Python
251 lines
6.4 KiB
Python
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"""
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Additional tests for PandasArray that aren't covered by
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the interface tests.
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"""
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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from pandas.arrays import PandasArray
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from pandas.core.arrays.numpy_ import PandasDtype
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@pytest.fixture(
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params=[
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np.array(["a", "b"], dtype=object),
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np.array([0, 1], dtype=float),
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np.array([0, 1], dtype=int),
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np.array([0, 1 + 2j], dtype=complex),
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np.array([True, False], dtype=bool),
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np.array([0, 1], dtype="datetime64[ns]"),
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np.array([0, 1], dtype="timedelta64[ns]"),
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]
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)
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def any_numpy_array(request):
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"""
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Parametrized fixture for NumPy arrays with different dtypes.
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This excludes string and bytes.
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"""
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return request.param
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# ----------------------------------------------------------------------------
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# PandasDtype
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@pytest.mark.parametrize(
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"dtype, expected",
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[
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("bool", True),
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("int", True),
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("uint", True),
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("float", True),
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("complex", True),
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("str", False),
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("bytes", False),
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("datetime64[ns]", False),
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("object", False),
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("void", False),
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],
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)
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def test_is_numeric(dtype, expected):
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dtype = PandasDtype(dtype)
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assert dtype._is_numeric is expected
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@pytest.mark.parametrize(
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"dtype, expected",
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[
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("bool", True),
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("int", False),
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("uint", False),
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("float", False),
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("complex", False),
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("str", False),
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("bytes", False),
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("datetime64[ns]", False),
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("object", False),
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("void", False),
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],
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)
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def test_is_boolean(dtype, expected):
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dtype = PandasDtype(dtype)
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assert dtype._is_boolean is expected
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def test_repr():
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dtype = PandasDtype(np.dtype("int64"))
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assert repr(dtype) == "PandasDtype('int64')"
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def test_constructor_from_string():
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result = PandasDtype.construct_from_string("int64")
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expected = PandasDtype(np.dtype("int64"))
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assert result == expected
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# ----------------------------------------------------------------------------
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# Construction
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def test_constructor_no_coercion():
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with pytest.raises(ValueError, match="NumPy array"):
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PandasArray([1, 2, 3])
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def test_series_constructor_with_copy():
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ndarray = np.array([1, 2, 3])
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ser = pd.Series(PandasArray(ndarray), copy=True)
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assert ser.values is not ndarray
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def test_series_constructor_with_astype():
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ndarray = np.array([1, 2, 3])
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result = pd.Series(PandasArray(ndarray), dtype="float64")
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expected = pd.Series([1.0, 2.0, 3.0], dtype="float64")
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tm.assert_series_equal(result, expected)
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def test_from_sequence_dtype():
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arr = np.array([1, 2, 3], dtype="int64")
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result = PandasArray._from_sequence(arr, dtype="uint64")
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expected = PandasArray(np.array([1, 2, 3], dtype="uint64"))
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tm.assert_extension_array_equal(result, expected)
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def test_constructor_copy():
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arr = np.array([0, 1])
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result = PandasArray(arr, copy=True)
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assert np.shares_memory(result._ndarray, arr) is False
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def test_constructor_with_data(any_numpy_array):
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nparr = any_numpy_array
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arr = PandasArray(nparr)
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assert arr.dtype.numpy_dtype == nparr.dtype
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# ----------------------------------------------------------------------------
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# Conversion
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def test_to_numpy():
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arr = PandasArray(np.array([1, 2, 3]))
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result = arr.to_numpy()
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assert result is arr._ndarray
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result = arr.to_numpy(copy=True)
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assert result is not arr._ndarray
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result = arr.to_numpy(dtype="f8")
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expected = np.array([1, 2, 3], dtype="f8")
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tm.assert_numpy_array_equal(result, expected)
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# ----------------------------------------------------------------------------
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# Setitem
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def test_setitem_series():
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ser = pd.Series([1, 2, 3])
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ser.array[0] = 10
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expected = pd.Series([10, 2, 3])
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tm.assert_series_equal(ser, expected)
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def test_setitem(any_numpy_array):
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nparr = any_numpy_array
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arr = PandasArray(nparr, copy=True)
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arr[0] = arr[1]
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nparr[0] = nparr[1]
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tm.assert_numpy_array_equal(arr.to_numpy(), nparr)
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# ----------------------------------------------------------------------------
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# Reductions
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def test_bad_reduce_raises():
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arr = np.array([1, 2, 3], dtype="int64")
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arr = PandasArray(arr)
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msg = "cannot perform not_a_method with type int"
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with pytest.raises(TypeError, match=msg):
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arr._reduce(msg)
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def test_validate_reduction_keyword_args():
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arr = PandasArray(np.array([1, 2, 3]))
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msg = "the 'keepdims' parameter is not supported .*all"
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with pytest.raises(ValueError, match=msg):
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arr.all(keepdims=True)
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# ----------------------------------------------------------------------------
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# Ops
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def test_ufunc():
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arr = PandasArray(np.array([-1.0, 0.0, 1.0]))
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result = np.abs(arr)
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expected = PandasArray(np.abs(arr._ndarray))
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tm.assert_extension_array_equal(result, expected)
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r1, r2 = np.divmod(arr, np.add(arr, 2))
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e1, e2 = np.divmod(arr._ndarray, np.add(arr._ndarray, 2))
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e1 = PandasArray(e1)
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e2 = PandasArray(e2)
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tm.assert_extension_array_equal(r1, e1)
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tm.assert_extension_array_equal(r2, e2)
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def test_basic_binop():
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# Just a basic smoke test. The EA interface tests exercise this
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# more thoroughly.
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x = PandasArray(np.array([1, 2, 3]))
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result = x + x
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expected = PandasArray(np.array([2, 4, 6]))
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tm.assert_extension_array_equal(result, expected)
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@pytest.mark.parametrize("dtype", [None, object])
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def test_setitem_object_typecode(dtype):
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arr = PandasArray(np.array(["a", "b", "c"], dtype=dtype))
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arr[0] = "t"
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expected = PandasArray(np.array(["t", "b", "c"], dtype=dtype))
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tm.assert_extension_array_equal(arr, expected)
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def test_setitem_no_coercion():
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# https://github.com/pandas-dev/pandas/issues/28150
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arr = PandasArray(np.array([1, 2, 3]))
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with pytest.raises(ValueError, match="int"):
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arr[0] = "a"
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# With a value that we do coerce, check that we coerce the value
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# and not the underlying array.
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arr[0] = 2.5
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assert isinstance(arr[0], (int, np.integer)), type(arr[0])
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def test_setitem_preserves_views():
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# GH#28150, see also extension test of the same name
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arr = PandasArray(np.array([1, 2, 3]))
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view1 = arr.view()
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view2 = arr[:]
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view3 = np.asarray(arr)
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arr[0] = 9
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assert view1[0] == 9
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assert view2[0] == 9
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assert view3[0] == 9
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arr[-1] = 2.5
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view1[-1] = 5
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assert arr[-1] == 5
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