46 lines
1.1 KiB
Python
46 lines
1.1 KiB
Python
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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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from pandas.core.arrays.floating import Float32Dtype, Float64Dtype
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def test_dtypes(dtype):
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# smoke tests on auto dtype construction
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np.dtype(dtype.type).kind == "f"
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assert dtype.name is not None
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@pytest.mark.parametrize(
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"dtype, expected",
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[(Float32Dtype(), "Float32Dtype()"), (Float64Dtype(), "Float64Dtype()")],
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)
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def test_repr_dtype(dtype, expected):
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assert repr(dtype) == expected
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def test_repr_array():
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result = repr(pd.array([1.0, None, 3.0]))
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expected = "<FloatingArray>\n[1.0, <NA>, 3.0]\nLength: 3, dtype: Float64"
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assert result == expected
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def test_repr_array_long():
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data = pd.array([1.0, 2.0, None] * 1000)
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expected = """<FloatingArray>
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[ 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0,
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...
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<NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>]
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Length: 3000, dtype: Float64"""
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result = repr(data)
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assert result == expected
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def test_frame_repr(data_missing):
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df = pd.DataFrame({"A": data_missing})
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result = repr(df)
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expected = " A\n0 <NA>\n1 0.1"
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assert result == expected
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