52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
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import numpy as np
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import pytest
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from pandas.core.dtypes.common import is_integer_dtype
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import pandas as pd
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import pandas._testing as tm
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arrays = [pd.array([1, 2, 3, None], dtype=dtype) for dtype in tm.ALL_INT_EA_DTYPES]
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arrays += [
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pd.array([0.141, -0.268, 5.895, None], dtype=dtype) for dtype in tm.FLOAT_EA_DTYPES
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]
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@pytest.fixture(params=arrays, ids=[a.dtype.name for a in arrays])
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def data(request):
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"""
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Fixture returning parametrized 'data' array with different integer and
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floating point types
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"""
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return request.param
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@pytest.fixture()
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def numpy_dtype(data):
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"""
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Fixture returning numpy dtype from 'data' input array.
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"""
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# For integer dtype, the numpy conversion must be done to float
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if is_integer_dtype(data):
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numpy_dtype = float
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else:
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numpy_dtype = data.dtype.type
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return numpy_dtype
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def test_round(data, numpy_dtype):
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# No arguments
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result = data.round()
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expected = pd.array(
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np.round(data.to_numpy(dtype=numpy_dtype, na_value=None)), dtype=data.dtype
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)
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tm.assert_extension_array_equal(result, expected)
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# Decimals argument
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result = data.round(decimals=2)
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expected = pd.array(
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np.round(data.to_numpy(dtype=numpy_dtype, na_value=None), decimals=2),
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dtype=data.dtype,
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)
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tm.assert_extension_array_equal(result, expected)
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