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How to use test_inferred_dtype method in pandera

Best Python code snippet using pandera_python

test_dtype.py

Source:test_dtype.py

...9    ('object', np.nan),10    ('datetime64[ns]', pd.NaT),11    ('timedelta64[ns]', pd.NaT),12])13def test_inferred_dtype(dtype, fill_value):14    sparse_dtype = SparseDtype(dtype)15    result = sparse_dtype.fill_value16    if pd.isna(fill_value):17        assert pd.isna(result) and type(result) == type(fill_value)18    else:19        assert result == fill_value20def test_from_sparse_dtype():21    dtype = SparseDtype('float', 0)22    result = SparseDtype(dtype)23    assert result.fill_value == 024def test_from_sparse_dtype_fill_value():25    dtype = SparseDtype('int', 1)26    result = SparseDtype(dtype, fill_value=2)27    expected = SparseDtype('int', 2)...

test_dtype.pyi

Source:test_dtype.pyi

...7# pylint: disable=super-init-not-called,abstract-method,redefined-builtin8# pylint: disable=unused-import,useless-import-alias,signature-differs9# pylint: disable=blacklisted-name,c-extension-no-member,import-error10from typing import Any11def test_inferred_dtype(dtype: Any, fill_value: Any) -> None:12    ...13def test_from_sparse_dtype() -> None:14    ...15def test_from_sparse_dtype_fill_value() -> None:16    ...17def test_equal(dtype: Any, fill_value: Any) -> None:18    ...19def test_nans_equal() -> None:20    ...21def test_not_equal(a: Any, b: Any) -> None:22    ...23def test_construct_from_string_raises() -> None:24    ...25def test_is_numeric(dtype: Any, expected: Any) -> None:...

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