How to use test_inferred_dtype method in pandera

Best Python code snippet using pandera_python

test_dtype.py

Source:test_dtype.py Github

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...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)...

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test_dtype.pyi

Source:test_dtype.pyi Github

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...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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