diff --git a/torch_frame/data/stats.py b/torch_frame/data/stats.py
index fbf6b633..6974a710 100644
--- a/torch_frame/data/stats.py
+++ b/torch_frame/data/stats.py
@@ -85,7 +85,8 @@ def compute(
         sep: str | None = None,
     ) -> Any:
         if self == StatType.MEAN:
-            flattened = np.hstack(np.hstack(ser.values))
+            val = np.hstack(ser.values) if ser.values.ndim > 1 else ser.values
+            flattened = np.hstack(val) if val.ndim > 1 else val
             finite_mask = np.isfinite(flattened)
             if not finite_mask.any():
                 # NOTE: We may just error out here if eveything is NaN
@@ -93,14 +94,16 @@ def compute(
             return np.mean(flattened[finite_mask]).item()
 
         elif self == StatType.STD:
-            flattened = np.hstack(np.hstack(ser.values))
+            val = np.hstack(ser.values) if ser.values.ndim > 1 else ser.values
+            flattened = np.hstack(val) if val.ndim > 1 else val
             finite_mask = np.isfinite(flattened)
             if not finite_mask.any():
                 return np.nan
             return np.std(flattened[finite_mask]).item()
 
         elif self == StatType.QUANTILES:
-            flattened = np.hstack(np.hstack(ser.values))
+            val = np.hstack(ser.values) if ser.values.ndim > 1 else ser.values
+            flattened = np.hstack(val) if val.ndim > 1 else val
             finite_mask = np.isfinite(flattened)
             if not finite_mask.any():
                 return [np.nan, np.nan, np.nan, np.nan, np.nan]