diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index 24a4b17ca3c..02231f26f61 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -71,6 +71,7 @@
     min_unsigned_type,
     np_to_pa_dtype,
     pandas_dtypes_to_cudf_dtypes,
+    pandas_dtypes_alias_to_cudf_alias,
 )
 from cudf.utils.utils import mask_dtype
 
@@ -881,14 +882,13 @@ def astype(self, dtype: Dtype, **kwargs) -> ColumnBase:
         if is_categorical_dtype(dtype):
             return self.as_categorical_column(dtype, **kwargs)
 
-        dtype = pandas_dtypes_to_cudf_dtypes.get(dtype, dtype)
+        dtype = (
+            pandas_dtypes_alias_to_cudf_alias.get(dtype, dtype)
+            if isinstance(dtype, str)
+            else pandas_dtypes_to_cudf_dtypes.get(dtype, dtype)
+        )
         if _is_non_decimal_numeric_dtype(dtype):
-            try:
-                return self.as_numerical_column(dtype, **kwargs)
-            except TypeError:
-                return self.as_numerical_column(
-                    self.convert_alias(dtype), **kwargs
-                )
+            return self.as_numerical_column(dtype, **kwargs)
         elif is_categorical_dtype(dtype):
             return self.as_categorical_column(dtype, **kwargs)
         elif pandas_dtype(dtype).type in {
@@ -968,20 +968,6 @@ def as_numerical_column(
     ) -> "cudf.core.column.NumericalColumn":
         raise NotImplementedError
 
-    def convert_alias(self, dtype):
-        aliases = {
-            "UInt8": "uint8",
-            "UInt16": "uint16",
-            "UInt32": "uint32",
-            "UInt64": "uint64",
-            "Int8": "int8",
-            "Int16": "int16",
-            "Int32": "int32",
-            "Int64": "int64",
-            "boolean": "bool",
-        }
-        return aliases[dtype]
-
     def as_datetime_column(
         self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.DatetimeColumn":
diff --git a/python/cudf/cudf/tests/test_column.py b/python/cudf/cudf/tests/test_column.py
index 11b2e4bc9f9..761b2f32f18 100644
--- a/python/cudf/cudf/tests/test_column.py
+++ b/python/cudf/cudf/tests/test_column.py
@@ -495,6 +495,8 @@ def test_concatenate_large_column_strings():
         ("Int32", "int32"),
         ("Int64", "int64"),
         ("boolean", "bool"),
+        ("Float32", "float32"),
+        ("Float64", "float64"),
     ],
 )
 @pytest.mark.parametrize(
diff --git a/python/cudf/cudf/utils/dtypes.py b/python/cudf/cudf/utils/dtypes.py
index e1ae87e5089..46bd1b449c4 100644
--- a/python/cudf/cudf/utils/dtypes.py
+++ b/python/cudf/cudf/utils/dtypes.py
@@ -92,11 +92,25 @@
     pd.StringDtype(): np.dtype("object"),
 }
 
+pandas_dtypes_alias_to_cudf_alias = {
+    "UInt8": "uint8",
+    "UInt16": "uint16",
+    "UInt32": "uint32",
+    "UInt64": "uint64",
+    "Int8": "int8",
+    "Int16": "int16",
+    "Int32": "int32",
+    "Int64": "int64",
+    "boolean": "bool",
+}
+
 if PANDAS_GE_120:
     cudf_dtypes_to_pandas_dtypes[np.dtype("float32")] = pd.Float32Dtype()
     cudf_dtypes_to_pandas_dtypes[np.dtype("float64")] = pd.Float64Dtype()
     pandas_dtypes_to_cudf_dtypes[pd.Float32Dtype()] = np.dtype("float32")
     pandas_dtypes_to_cudf_dtypes[pd.Float64Dtype()] = np.dtype("float64")
+    pandas_dtypes_alias_to_cudf_alias["Float32"] = "float32"
+    pandas_dtypes_alias_to_cudf_alias["Float64"] = "float64"
 
 SIGNED_INTEGER_TYPES = {"int8", "int16", "int32", "int64"}
 UNSIGNED_TYPES = {"uint8", "uint16", "uint32", "uint64"}