From 30eed73023b060a610b6526b5bcde989c50dee52 Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Sun, 16 Jan 2022 13:48:53 -0800
Subject: [PATCH] REF: share NumericIndex.astype+Index.astype

---
 pandas/core/indexes/base.py    | 30 +++++++++++++++++++++++++++++-
 pandas/core/indexes/numeric.py | 32 --------------------------------
 2 files changed, 29 insertions(+), 33 deletions(-)

diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 2c5cbef9f86c2..ae2f3bf6255bc 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -51,6 +51,7 @@
 from pandas.compat.numpy import function as nv
 from pandas.errors import (
     DuplicateLabelError,
+    IntCastingNaNError,
     InvalidIndexError,
 )
 from pandas.util._decorators import (
@@ -64,6 +65,7 @@
     rewrite_exception,
 )
 
+from pandas.core.dtypes.astype import astype_nansafe
 from pandas.core.dtypes.cast import (
     can_hold_element,
     common_dtype_categorical_compat,
@@ -1050,6 +1052,14 @@ def astype(self, dtype, copy: bool = True):
             with rewrite_exception(type(values).__name__, type(self).__name__):
                 new_values = values.astype(dtype, copy=copy)
 
+        elif is_float_dtype(self.dtype) and needs_i8_conversion(dtype):
+            # NB: this must come before the ExtensionDtype check below
+            # TODO: this differs from Series behavior; can/should we align them?
+            raise TypeError(
+                f"Cannot convert Float64Index to dtype {dtype}; integer "
+                "values are required for conversion"
+            )
+
         elif isinstance(dtype, ExtensionDtype):
             cls = dtype.construct_array_type()
             # Note: for RangeIndex and CategoricalDtype self vs self._values
@@ -1058,13 +1068,31 @@ def astype(self, dtype, copy: bool = True):
 
         else:
             try:
-                new_values = values.astype(dtype, copy=copy)
+                if dtype == str:
+                    # GH#38607
+                    new_values = values.astype(dtype, copy=copy)
+                else:
+                    # GH#13149 specifically use astype_nansafe instead of astype
+                    new_values = astype_nansafe(values, dtype=dtype, copy=copy)
+            except IntCastingNaNError:
+                raise
             except (TypeError, ValueError) as err:
+                if dtype.kind == "u" and "losslessly" in str(err):
+                    # keep the message from _astype_float_to_int_nansafe
+                    raise
                 raise TypeError(
                     f"Cannot cast {type(self).__name__} to dtype {dtype}"
                 ) from err
 
         # pass copy=False because any copying will be done in the astype above
+        if self._is_backward_compat_public_numeric_index:
+            # this block is needed so e.g. NumericIndex[int8].astype("int32") returns
+            # NumericIndex[int32] and not Int64Index with dtype int64.
+            # When Int64Index etc. are removed from the code base, removed this also.
+            if isinstance(dtype, np.dtype) and is_numeric_dtype(dtype):
+                return self._constructor(
+                    new_values, name=self.name, dtype=dtype, copy=False
+                )
         return Index(new_values, name=self.name, dtype=new_values.dtype, copy=False)
 
     _index_shared_docs[
diff --git a/pandas/core/indexes/numeric.py b/pandas/core/indexes/numeric.py
index ffd511b92da43..53bea5e6ff6b0 100644
--- a/pandas/core/indexes/numeric.py
+++ b/pandas/core/indexes/numeric.py
@@ -23,10 +23,8 @@
 )
 from pandas.util._exceptions import find_stack_level
 
-from pandas.core.dtypes.astype import astype_nansafe
 from pandas.core.dtypes.common import (
     is_dtype_equal,
-    is_extension_array_dtype,
     is_float,
     is_float_dtype,
     is_integer_dtype,
@@ -34,7 +32,6 @@
     is_scalar,
     is_signed_integer_dtype,
     is_unsigned_integer_dtype,
-    needs_i8_conversion,
     pandas_dtype,
 )
 from pandas.core.dtypes.generic import ABCSeries
@@ -232,35 +229,6 @@ def __contains__(self, key) -> bool:
         except (OverflowError, TypeError, ValueError):
             return False
 
-    @doc(Index.astype)
-    def astype(self, dtype, copy: bool = True):
-        dtype = pandas_dtype(dtype)
-        if is_float_dtype(self.dtype):
-            if needs_i8_conversion(dtype):
-                raise TypeError(
-                    f"Cannot convert Float64Index to dtype {dtype}; integer "
-                    "values are required for conversion"
-                )
-            elif is_integer_dtype(dtype) and not is_extension_array_dtype(dtype):
-                # TODO(ExtensionIndex); this can change once we have an EA Index type
-                # GH 13149
-                arr = astype_nansafe(self._values, dtype=dtype)
-                if isinstance(self, Float64Index):
-                    if dtype.kind == "i":
-                        return Int64Index(arr, name=self.name)
-                    else:
-                        return UInt64Index(arr, name=self.name)
-                else:
-                    return NumericIndex(arr, name=self.name, dtype=dtype)
-        elif self._is_backward_compat_public_numeric_index:
-            # this block is needed so e.g. NumericIndex[int8].astype("int32") returns
-            # NumericIndex[int32] and not Int64Index with dtype int64.
-            # When Int64Index etc. are removed from the code base, removed this also.
-            if not is_extension_array_dtype(dtype) and is_numeric_dtype(dtype):
-                return self._constructor(self, dtype=dtype, copy=copy)
-
-        return super().astype(dtype, copy=copy)
-
     # ----------------------------------------------------------------
     # Indexing Methods