@@ -39,11 +39,9 @@
 
 from sdc.datatypes.range_index_type import RangeIndexType
 from sdc.datatypes.int64_index_type import Int64IndexType
-from sdc.datatypes.common_functions import SDCLimitation, _sdc_take
 from sdc.utilities.utils import sdc_overload, sdc_overload_attribute, sdc_overload_method
 from sdc.utilities.sdc_typing_utils import TypeChecker, check_is_numeric_array, check_signed_integer
-from sdc.functions.numpy_like import getitem_by_mask
-from sdc.functions.numpy_like import astype as nplike_astype
+from sdc.functions import numpy_like
 from numba.core.boxing import box_array, unbox_array
 from sdc.hiframes.api import fix_df_index
 from sdc.extensions.indexes.indexes_generic import _check_dtype_param_type
@@ -128,7 +126,7 @@ def pd_int64_index_ctor_impl(data, dtype=None, copy=False, name=None):
             _data = fix_df_index(data)._data
 
         if data_dtype_is_int64 == False:  # noqa
-            _data = nplike_astype(_data, dtype=types.int64)
+            _data = numpy_like.astype(_data, dtype=types.int64)
         else:
             if copy:
                 _data = np.copy(_data)
@@ -291,7 +289,8 @@ def pd_int64_index_copy_overload(self, name=None, deep=False, dtype=None):
     def pd_int64_index_copy_impl(self, name=None, deep=False, dtype=None):
 
         _name = self._name if keep_name == True else name  # noqa
-        return init_int64_index(self._data, _name)
+        new_index_data = self._data if not deep else numpy_like.copy(self._data)
+        return init_int64_index(new_index_data, _name)
 
     return pd_int64_index_copy_impl
 
@@ -408,6 +407,10 @@ def pd_int64_index_ravel_overload(self, order='C'):
         raise TypingError('{} Unsupported parameters. Given order: {}'.format(_func_name, order))
 
     def pd_int64_index_ravel_impl(self, order='C'):
+        # np.ravel argument order is not supported in Numba
+        if order != 'C':
+            raise ValueError(f"Unsupported value for argument 'order' (only default 'C' is supported)")
+
         return self.values
 
     return pd_int64_index_ravel_impl
@@ -459,11 +459,14 @@ def pd_range_index_ravel_overload(self, order='C'):
 
     _func_name = 'Method ravel().'
 
-    # np.ravel argument order is not supported in Numba
     if not (isinstance(order, (types.Omitted, types.StringLiteral, types.UnicodeType)) or order == 'C'):
         raise TypingError('{} Unsupported parameters. Given order: {}'.format(_func_name, order))
 
     def pd_range_index_ravel_impl(self, order='C'):
+        # np.ravel argument order is not supported in Numba
+        if order != 'C':
+            raise ValueError(f"Unsupported value for argument 'order' (only default 'C' is supported)")
+
         return self.values
 
     return pd_range_index_ravel_impl
@@ -194,6 +194,37 @@ def test_impl(index, value):
                 result_ref = test_impl(index, value)
                 np.testing.assert_array_equal(result, result_ref)
 
+    def test_int64_index_copy(self):
+        def test_impl(index, new_name):
+            return index.copy(name=new_name)
+        sdc_func = self.jit(test_impl)
+
+        for data in _generate_valid_int64_index_data():
+            for name, new_name in product(test_global_index_names, repeat=2):
+                index = pd.Int64Index(data, name=name)
+                with self.subTest(index=index, new_name=new_name):
+                    result = sdc_func(index, new_name)
+                    result_ref = test_impl(index, new_name)
+                    pd.testing.assert_index_equal(result, result_ref)
+
+    def test_int64_index_copy_param_deep(self):
+        def test_impl(index, deep):
+            return index.copy(deep=deep)
+        sdc_func = self.jit(test_impl)
+
+        index = pd.Int64Index([1, 11, 2])
+        for deep in [True, False]:
+            with self.subTest(deep=deep):
+                result = sdc_func(index, deep)
+                result_ref = test_impl(index, deep)
+                pd.testing.assert_index_equal(result, result_ref)
+                # pandas uses ndarray views when copies index, so for python
+                # case check that data arrays share the same memory
+                self.assertEqual(
+                    result._data is index._data,
+                    result_ref._data.base is index._data
+                )
+
     def test_int64_index_getitem_scalar(self):
         def test_impl(index, idx):
             return index[idx]