diff --git a/marimo/_plugins/ui/_impl/dataframes/transforms/apply.py b/marimo/_plugins/ui/_impl/dataframes/transforms/apply.py
index ca469c6f909..5a30640f614 100644
--- a/marimo/_plugins/ui/_impl/dataframes/transforms/apply.py
+++ b/marimo/_plugins/ui/_impl/dataframes/transforms/apply.py
@@ -19,43 +19,40 @@
 )
 from marimo._utils.assert_never import assert_never
 
+_transform_type_to_handler_method = {
+    TransformType.COLUMN_CONVERSION: "handle_column_conversion",
+    TransformType.RENAME_COLUMN: "handle_rename_column",
+    TransformType.SORT_COLUMN: "handle_sort_column",
+    TransformType.FILTER_ROWS: "handle_filter_rows",
+    TransformType.GROUP_BY: "handle_group_by",
+    TransformType.AGGREGATE: "handle_aggregate",
+    TransformType.SELECT_COLUMNS: "handle_select_columns",
+    TransformType.SHUFFLE_ROWS: "handle_shuffle_rows",
+    TransformType.SAMPLE_ROWS: "handle_sample_rows",
+    TransformType.EXPLODE_COLUMNS: "handle_explode_columns",
+    TransformType.EXPAND_DICT: "handle_expand_dict",
+    TransformType.UNIQUE: "handle_unique",
+}
+
 T = TypeVar("T")
 
 
 def _handle(df: T, handler: TransformHandler[T], transform: Transform) -> T:
-    if transform.type is TransformType.COLUMN_CONVERSION:
-        return handler.handle_column_conversion(df, transform)
-    if transform.type is TransformType.RENAME_COLUMN:
-        return handler.handle_rename_column(df, transform)
-    if transform.type is TransformType.SORT_COLUMN:
-        return handler.handle_sort_column(df, transform)
-    if transform.type is TransformType.FILTER_ROWS:
-        return handler.handle_filter_rows(df, transform)
-    if transform.type is TransformType.GROUP_BY:
-        return handler.handle_group_by(df, transform)
-    if transform.type is TransformType.AGGREGATE:
-        return handler.handle_aggregate(df, transform)
-    if transform.type is TransformType.SELECT_COLUMNS:
-        return handler.handle_select_columns(df, transform)
-    if transform.type is TransformType.SHUFFLE_ROWS:
-        return handler.handle_shuffle_rows(df, transform)
-    if transform.type is TransformType.SAMPLE_ROWS:
-        return handler.handle_sample_rows(df, transform)
-    if transform.type is TransformType.EXPLODE_COLUMNS:
-        return handler.handle_explode_columns(df, transform)
-    if transform.type is TransformType.EXPAND_DICT:
-        return handler.handle_expand_dict(df, transform)
-    if transform.type is TransformType.UNIQUE:
-        return handler.handle_unique(df, transform)
+    method_name = _transform_type_to_handler_method.get(transform.type)
+    if method_name is not None:
+        # Avoid attribute lookup by pre-binding all handler methods (if desired for even faster)
+        # But attribute lookup here is acceptable and efficient
+        return getattr(handler, method_name)(df, transform)
     assert_never(transform.type)
 
 
 def _apply_transforms(
     df: T, handler: TransformHandler[T], transforms: Transformations
 ) -> T:
-    if not transforms.transforms:
+    transforms_list = transforms.transforms
+    if not transforms_list:
         return df
-    for transform in transforms.transforms:
+    for transform in transforms_list:
         df = _handle(df, handler, transform)
     return df