BUG: remove part of error handler pandas-dev#40729

Author: junjunjunk

pandas/core/arrays/floating.py

@@ -10,10 +10,7 @@
 
 import numpy as np
 
-from pandas._libs import (
-    lib,
-    missing as libmissing,
-)
+from pandas._libs import missing as libmissing
 from pandas._typing import (
     ArrayLike,
     DtypeObj,
@@ -28,7 +25,6 @@
     is_float_dtype,
     is_integer_dtype,
     is_list_like,
-    is_object_dtype,
     pandas_dtype,
 )
 from pandas.core.dtypes.dtypes import (
@@ -134,21 +130,7 @@ def coerce_to_array(
         return values, mask
 
     values = np.array(values, copy=copy)
-    if is_object_dtype(values):
-        inferred_type = lib.infer_dtype(values, skipna=True)
-        if inferred_type == "empty":
-            values = np.empty(len(values))
-            values.fill(np.nan)
-        elif inferred_type not in [
-            "floating",
-            "integer",
-            "mixed-integer",
-            "integer-na",
-            "mixed-integer-float",
-        ]:
-            raise TypeError(f"{values.dtype} cannot be converted to a FloatingDtype")
-
-    elif is_bool_dtype(values) and is_float_dtype(dtype):
+    if is_bool_dtype(values) and is_float_dtype(dtype):
         values = np.array(values, dtype=float, copy=copy)
 
     elif not (is_integer_dtype(values) or is_float_dtype(values)):

pandas/core/arrays/integer.py

@@ -35,7 +35,6 @@
     is_float_dtype,
     is_integer_dtype,
     is_list_like,
-    is_object_dtype,
     pandas_dtype,
 )
 from pandas.core.dtypes.missing import isna
@@ -190,21 +189,7 @@ def coerce_to_array(
         return values, mask
 
     values = np.array(values, copy=copy)
-    if is_object_dtype(values):
-        inferred_type = lib.infer_dtype(values, skipna=True)
-        if inferred_type == "empty":
-            values = np.empty(len(values))
-            values.fill(np.nan)
-        elif inferred_type not in [
-            "floating",
-            "integer",
-            "mixed-integer",
-            "integer-na",
-            "mixed-integer-float",
-        ]:
-            raise TypeError(f"{values.dtype} cannot be converted to an IntegerDtype")
-
-    elif is_bool_dtype(values) and is_integer_dtype(dtype):
+    if is_bool_dtype(values) and is_integer_dtype(dtype):
         values = np.array(values, dtype=int, copy=copy)
 
     elif not (is_integer_dtype(values) or is_float_dtype(values)):

pandas/tests/arrays/string_/test_string.py

@@ -363,6 +363,10 @@ def test_astype_int(dtype, request):
     expected = pd.array([1, pd.NA, 3], dtype="Int64")
     tm.assert_extension_array_equal(result, expected)
 
+    result = pd.Series(["1", "2", "3", "4"], dtype="Int64")
+    expected = pd.Series([1, 2, 3, 4], dtype="Int64")
+    tm.assert_series_equal(result, expected)
+
 
 def test_astype_float(dtype, any_float_allowed_nullable_dtype, request):
     # Don't compare arrays (37974)
@@ -383,6 +387,10 @@ def test_astype_float(dtype, any_float_allowed_nullable_dtype, request):
     expected = pd.Series([1.1, np.nan, 3.3], dtype=any_float_allowed_nullable_dtype)
     tm.assert_series_equal(result, expected)
 
+    result = pd.Series(["1", "2", "3", "4"], dtype="Float64")
+    expected = pd.Series([1, 2, 3, 4], dtype="Float64")
+    tm.assert_series_equal(result, expected)
+
 
 @pytest.mark.parametrize("skipna", [True, False])
 @pytest.mark.xfail(reason="Not implemented StringArray.sum")