Update stack size filtering in app.py to drop missing values

- Added a dropna() method to the stack size filtering logic to remove rows with missing values in the 'stack_size' column, enhancing data integrity during filtering operations.

app.py

@@ -261,7 +261,9 @@ with tab2:
                     if stack_parse_var == 'Specific' and stack_names:
                         working_df = working_df[working_df['stack'].isin(stack_names)]
                     if low_stack_size_var and high_stack_size_var:
+                        working_df = working_df.dropna(subset=['stack_size'])
                         working_df = working_df[working_df['stack_size'].between(low_stack_size_var, high_stack_size_var)]
+                        
                     # if player_parse_var == 'Specific' and player_names:
                     #     working_df = working_df[working_df['BaseName'].isin(player_names)]
                     if low_entries_var and high_entries_var: