diff --git a/CHANGELOG.md b/CHANGELOG.md
index 53101ae1853..de705dcb915 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -41,6 +41,7 @@
 - PR #6118 Fix Java build for ORC read args change and update package version
 - PR #6121 Replace calls to get_default_resource with get_current_device_resource
 - PR #6128 Add support for numpy RandomState handling in `sample`
+- PR #6154 Warnings on row-wise op only when non-numeric columns are found.
 - PR #6150 Fix issue related to inferring `datetime64` format with UTC timezone in string data
 
 
@@ -205,12 +206,12 @@
 - PR #5602 Add support for concatenation of `Series` & `DataFrame` in `cudf.concat` when `axis=0`
 - PR #5603 Refactor JIT `parser.cpp`
 - PR #5643 Update `isort` to 5.0.4
-- PR #5648 OO interface for hash join with explicit `build/probe` semantic 
+- PR #5648 OO interface for hash join with explicit `build/probe` semantic
 - PR #5662 Make Java ColumnVector(long nativePointer) constructor public
 - PR #5681 Pin black, flake8 and isort
 - PR #5679 Use `pickle5` to test older Python versions
 - PR #5684 Use `pickle5` in `Serializable` (when available)
-- PR #5419 Support rolling, groupby_rolling for durations 
+- PR #5419 Support rolling, groupby_rolling for durations
 - PR #5687 Change strings::split_record to return a lists column
 - PR #5708 Add support for `dummy_na` in `get_dummies`
 - PR #5709 Update java build to help cu-spacial with java bindings
diff --git a/python/cudf/cudf/core/dataframe.py b/python/cudf/cudf/core/dataframe.py
index 685f04cb14b..eca8b85c03d 100644
--- a/python/cudf/cudf/core/dataframe.py
+++ b/python/cudf/cudf/core/dataframe.py
@@ -5344,10 +5344,6 @@ def isin(self, values):
     def _prepare_for_rowwise_op(self):
         """Prepare a DataFrame for CuPy-based row-wise operations.
         """
-        warnings.warn(
-            "Row-wise operations currently only support int, float, "
-            "and bool dtypes."
-        )
 
         if any([col.nullable for col in self._columns]):
             msg = (
@@ -5359,6 +5355,12 @@ def _prepare_for_rowwise_op(self):
 
         filtered = self.select_dtypes(include=[np.number, np.bool])
         common_dtype = np.find_common_type(filtered.dtypes, [])
+        if filtered._num_columns < self._num_columns:
+            msg = (
+                "Row-wise operations currently only support int, float "
+                "and bool dtypes. Non numeric columns are ignored."
+            )
+            warnings.warn(msg)
         coerced = filtered.astype(common_dtype)
         return coerced