Update app.py

app.py

@@ -534,20 +534,22 @@ elif app_mode == "Data Cleaning":
         data_to_encode = st.multiselect("Select categorical columns to encode", df.select_dtypes(include='object').columns)
         if data_to_encode:
             if st.button("Apply Encoding"):
-                new_df = df.copy()
-                if encoding_method == "Label Encoding":
-                    label_encoders = {}
-                    for col in data_to_encode:
-                        le = LabelEncoder()
-                        new_df[col] = le.fit_transform(new_df[col].astype(str))
-                        label_encoders[col] = le
-                elif encoding_method == "One-Hot Encoding":
-                    new_df = pd.get_dummies(new_df, columns=data_to_encode, drop_first=True)
-                
-                update_cleaned_data(new_df)
-                st.rerun() # Force re-run after apply
-            except Exception as e:
+                try:
+                    new_df = df.copy()
+                    if encoding_method == "Label Encoding":
+                        label_encoders = {}
+                        for col in data_to_encode:
+                            le = LabelEncoder()
+                            new_df[col] = le.fit_transform(new_df[col].astype(str))
+                            label_encoders[col] = le
+                    elif encoding_method == "One-Hot Encoding":
+                        new_df = pd.get_dummies(new_df, columns=data_to_encode, drop_first=True)
+                    
+                    update_cleaned_data(new_df)
+                    st.rerun()  # Force re-run after apply
+                except Exception as e:
                     st.error(f"Error: {str(e)}")
+
             
 
     # --------------------------