remove all python_numpy usage

Author: jorisvandenbossche

pandas/conftest.py

@@ -1295,7 +1295,6 @@ def nullable_string_dtype(request):
 @pytest.fixture(
     params=[
         "python",
-        "python_numpy",
         pytest.param("pyarrow", marks=td.skip_if_no("pyarrow")),
     ]
 )
@@ -1314,6 +1313,7 @@ def string_storage(request):
         ("python", pd.NA),
         pytest.param(("pyarrow", pd.NA), marks=td.skip_if_no("pyarrow")),
         pytest.param(("pyarrow", np.nan), marks=td.skip_if_no("pyarrow")),
+        ("python", np.nan),
     ]
 )
 def string_dtype_arguments(request):

pandas/core/arrays/string_.py

@@ -146,10 +146,6 @@ def __init__(
             # TODO raise a deprecation warning
             storage = "pyarrow"
             na_value = np.nan
-        if storage == "python_numpy":
-            # TODO remove
-            storage = "python"
-            na_value = np.nan
 
         # validate options
         if storage not in {"python", "pyarrow"}:
@@ -234,9 +230,6 @@ def construct_from_string(cls, string) -> Self:
             return cls()
         elif string == "string[python]":
             return cls(storage="python")
-        elif string == "string[python_numpy]":
-            # TODO remove
-            return cls(storage="python", na_value=np.nan)
         elif string == "string[pyarrow]":
             return cls(storage="pyarrow")
         elif string == "string[pyarrow_numpy]":

pandas/tests/strings/test_find_replace.py

@@ -232,18 +232,14 @@ def test_contains_nan(any_string_dtype):
     expected = Series([True, True, True], dtype=expected_dtype)
     tm.assert_series_equal(result, expected)
 
-    if any_string_dtype == "string[python_numpy]":
-        with pytest.raises(TypeError):
-            result = s.str.contains("foo", na="foo")
+    result = s.str.contains("foo", na="foo")
+    if any_string_dtype == "object":
+        expected = Series(["foo", "foo", "foo"], dtype=np.object_)
+    elif any_string_dtype.na_value is np.nan:
+        expected = Series([True, True, True], dtype=np.bool_)
     else:
-        result = s.str.contains("foo", na="foo")
-        if any_string_dtype == "object":
-            expected = Series(["foo", "foo", "foo"], dtype=np.object_)
-        elif any_string_dtype == "string[pyarrow_numpy]":
-            expected = Series([True, True, True], dtype=np.bool_)
-        else:
-            expected = Series([True, True, True], dtype="boolean")
-        tm.assert_series_equal(result, expected)
+        expected = Series([True, True, True], dtype="boolean")
+    tm.assert_series_equal(result, expected)
 
     result = s.str.contains("foo")
     expected_dtype = (