BUG: accept strings in FloatingArray._from_sequence (#45424)

Author: jbrockmendel

doc/source/whatsnew/v1.5.0.rst

@@ -200,6 +200,7 @@ Conversion
 - Bug in constructing a :class:`Series` from a float-containing list or a floating-dtype ndarray-like (e.g. ``dask.Array``) and an integer dtype raising instead of casting like we would with an ``np.ndarray`` (:issue:`40110`)
 - Bug in :meth:`Float64Index.astype` to unsigned integer dtype incorrectly casting to ``np.int64`` dtype (:issue:`45309`)
 - Bug in :meth:`Series.astype` and :meth:`DataFrame.astype` from floating dtype to unsigned integer dtype failing to raise in the presence of negative values (:issue:`45151`)
+- Bug in :func:`array` with ``FloatingDtype`` and values containing float-castable strings incorrectly raising (:issue:`45424`)
 -
 
 Strings

pandas/core/arrays/floating.py

@@ -14,6 +14,7 @@
     is_float_dtype,
     is_integer_dtype,
     is_object_dtype,
+    is_string_dtype,
 )
 from pandas.core.dtypes.dtypes import register_extension_dtype
 
@@ -112,7 +113,7 @@ def coerce_to_array(
         return values, mask
 
     values = np.array(values, copy=copy)
-    if is_object_dtype(values.dtype):
+    if is_object_dtype(values.dtype) or is_string_dtype(values.dtype):
         inferred_type = lib.infer_dtype(values, skipna=True)
         if inferred_type == "empty":
             pass

pandas/tests/arrays/categorical/test_astype.py

@@ -23,6 +23,16 @@ def test_astype_str_int_categories_to_nullable_int(self):
         expected = array(codes, dtype="Int64")
         tm.assert_extension_array_equal(res, expected)
 
+    def test_astype_str_int_categories_to_nullable_float(self):
+        # GH#39616
+        dtype = CategoricalDtype([str(i / 2) for i in range(5)])
+        codes = np.random.randint(5, size=20)
+        arr = Categorical.from_codes(codes, dtype=dtype)
+
+        res = arr.astype("Float64")
+        expected = array(codes, dtype="Float64") / 2
+        tm.assert_extension_array_equal(res, expected)
+
     @pytest.mark.parametrize("ordered", [True, False])
     def test_astype(self, ordered):
         # string

pandas/tests/arrays/floating/test_construction.py

@@ -112,7 +112,6 @@ def test_to_array_mixed_integer_float():
     "values",
     [
         ["foo", "bar"],
-        ["1", "2"],
         "foo",
         1,
         1.0,
@@ -132,12 +131,25 @@ def test_to_array_error(values):
             "values must be a 1D list-like",
             "Cannot pass scalar",
             r"float\(\) argument must be a string or a (real )?number, not 'dict'",
+            "could not convert string to float: 'foo'",
         ]
     )
     with pytest.raises((TypeError, ValueError), match=msg):
         pd.array(values, dtype="Float64")
 
 
+@pytest.mark.parametrize("values", [["1", "2", None], ["1.5", "2", None]])
+def test_construct_from_float_strings(values):
+    # see also test_to_integer_array_str
+    expected = pd.array([float(values[0]), 2, None], dtype="Float64")
+
+    res = pd.array(values, dtype="Float64")
+    tm.assert_extension_array_equal(res, expected)
+
+    res = FloatingArray._from_sequence(values)
+    tm.assert_extension_array_equal(res, expected)
+
+
 def test_to_array_inferred_dtype():
     # if values has dtype -> respect it
     result = pd.array(np.array([1, 2], dtype="float32"))