diff --git a/python/dalex/NEWS.md b/python/dalex/NEWS.md
index eb89ebb96..1bdf6b2b8 100644
--- a/python/dalex/NEWS.md
+++ b/python/dalex/NEWS.md
@@ -3,6 +3,9 @@
 ### development
 
 * Fix an error occuring in `predict_profile()` when a DataFrame has MultiIndex in `pandas >= 1.3.0` ([#550](https://github.com/ModelOriented/DALEX/pull/550))
+* Fix gaussian `norm()` calculation in `model_profile()` from `pi*sqrt(2)` to `sqrt(2*pi)`
+* Potential fix for a warning (future error) between `prepare_numerical_categorical()` and `prepare_x()` with `pandas == 2.1.0`
+
 
 ### v1.6.0 (2023-02-16) 
 
diff --git a/python/dalex/dalex/model_explanations/_aggregated_profiles/utils.py b/python/dalex/dalex/model_explanations/_aggregated_profiles/utils.py
index 73a60d3b2..15ded497d 100644
--- a/python/dalex/dalex/model_explanations/_aggregated_profiles/utils.py
+++ b/python/dalex/dalex/model_explanations/_aggregated_profiles/utils.py
@@ -99,7 +99,7 @@ def split_over_variables_and_labels(split_profile, type, groups, span):
 
 
 def norm(x, loc, scale):
-    return np.exp(-1 * ((x - loc) / scale) ** 2 / 2) / np.pi / np.sqrt(2) / scale
+    return np.exp(-1 * ((x - loc) / scale) ** 2 / 2) / np.sqrt(2 * np.pi) / scale
 
 
 def prepare_numerical_categorical(all_profiles, variables, variable_type):
@@ -122,7 +122,7 @@ def prepare_numerical_categorical(all_profiles, variables, variable_type):
         if vnames.shape[0] == 0:
             raise ValueError("There are no numerical variables")
 
-        all_profiles['_x_'] = 0
+        all_profiles['_x_'] = 0.0
 
     else:
         vnames = all_variables[~is_numeric]