diff --git a/pandas/_libs/missing.pxd b/pandas/_libs/missing.pxd index e32518864db0a..854dcf2ec9775 100644 --- a/pandas/_libs/missing.pxd +++ b/pandas/_libs/missing.pxd @@ -7,7 +7,6 @@ from numpy cimport ( cpdef bint is_matching_na(object left, object right, bint nan_matches_none=*) cpdef bint checknull(object val, bint inf_as_na=*) -cpdef bint checknull_old(object val) cpdef ndarray[uint8_t] isnaobj(ndarray arr, bint inf_as_na=*) cdef bint is_null_datetime64(v) diff --git a/pandas/_libs/missing.pyx b/pandas/_libs/missing.pyx index 6146e8ea13f89..2d66a655ba075 100644 --- a/pandas/_libs/missing.pyx +++ b/pandas/_libs/missing.pyx @@ -135,10 +135,6 @@ cdef inline bint is_decimal_na(object val): return isinstance(val, cDecimal) and val != val -cpdef bint checknull_old(object val): - return checknull(val, inf_as_na=True) - - @cython.wraparound(False) @cython.boundscheck(False) cpdef ndarray[uint8_t] isnaobj(ndarray arr, bint inf_as_na=False): @@ -176,12 +172,6 @@ cpdef ndarray[uint8_t] isnaobj(ndarray arr, bint inf_as_na=False): return result.view(np.bool_) -@cython.wraparound(False) -@cython.boundscheck(False) -def isnaobj_old(arr: ndarray) -> ndarray: - return isnaobj(arr, inf_as_na=True) - - @cython.wraparound(False) @cython.boundscheck(False) def isnaobj2d(arr: ndarray, inf_as_na: bool = False) -> ndarray: @@ -221,12 +211,6 @@ def isnaobj2d(arr: ndarray, inf_as_na: bool = False) -> ndarray: return result.view(np.bool_) -@cython.wraparound(False) -@cython.boundscheck(False) -def isnaobj2d_old(arr: ndarray) -> ndarray: - return isnaobj2d(arr, inf_as_na=True) - - def isposinf_scalar(val: object) -> bool: return util.is_float_object(val) and val == INF diff --git a/pandas/core/dtypes/missing.py b/pandas/core/dtypes/missing.py index 63b64dc504b52..d2733cddf8cee 100644 --- a/pandas/core/dtypes/missing.py +++ b/pandas/core/dtypes/missing.py @@ -158,10 +158,7 @@ def _isna(obj, inf_as_na: bool = False): boolean ndarray or boolean """ if is_scalar(obj): - if inf_as_na: - return libmissing.checknull_old(obj) - else: - return libmissing.checknull(obj) + return libmissing.checknull(obj, inf_as_na=inf_as_na) elif isinstance(obj, ABCMultiIndex): raise NotImplementedError("isna is not defined for MultiIndex") elif isinstance(obj, type): diff --git a/pandas/tests/dtypes/test_missing.py b/pandas/tests/dtypes/test_missing.py index 55d0e5e73418e..e04df7e43838f 100644 --- a/pandas/tests/dtypes/test_missing.py +++ b/pandas/tests/dtypes/test_missing.py @@ -565,21 +565,19 @@ def test_na_value_for_dtype(dtype, na_value): class TestNAObj: - - _1d_methods = ["isnaobj", "isnaobj_old"] - _2d_methods = ["isnaobj2d", "isnaobj2d_old"] - def _check_behavior(self, arr, expected): - for method in TestNAObj._1d_methods: - result = getattr(libmissing, method)(arr) - tm.assert_numpy_array_equal(result, expected) + result = libmissing.isnaobj(arr) + tm.assert_numpy_array_equal(result, expected) + result = libmissing.isnaobj(arr, inf_as_na=True) + tm.assert_numpy_array_equal(result, expected) arr = np.atleast_2d(arr) expected = np.atleast_2d(expected) - for method in TestNAObj._2d_methods: - result = getattr(libmissing, method)(arr) - tm.assert_numpy_array_equal(result, expected) + result = libmissing.isnaobj2d(arr) + tm.assert_numpy_array_equal(result, expected) + result = libmissing.isnaobj2d(arr, inf_as_na=True) + tm.assert_numpy_array_equal(result, expected) def test_basic(self): arr = np.array([1, None, "foo", -5.1, NaT, np.nan]) @@ -676,16 +674,16 @@ def test_checknull(self, func): def test_checknull_old(self): for value in na_vals + sometimes_na_vals: - assert libmissing.checknull_old(value) + assert libmissing.checknull(value, inf_as_na=True) for value in inf_vals: - assert libmissing.checknull_old(value) + assert libmissing.checknull(value, inf_as_na=True) for value in int_na_vals: - assert not libmissing.checknull_old(value) + assert not libmissing.checknull(value, inf_as_na=True) for value in never_na_vals: - assert not libmissing.checknull_old(value) + assert not libmissing.checknull(value, inf_as_na=True) def test_is_null_datetimelike(self): for value in na_vals: