Update app.py

app.py

@@ -11,36 +11,21 @@ def compare_csv_files():
     merged_df["CharacterErrorRate_Diff"] = merged_df["CharacterErrorRate_1.5"] - merged_df["CharacterErrorRate_1.4"]
     
     merged_df["WordErrorRate_Comparison"] = merged_df["WordErrorRate_Diff"].apply(
-        lambda x: f"1.5 is stronger than 1.4 ({x:.8f})" if x > 0 else (
-            f"1.4 is stronger than 1.5 ({-x:.8f})" if x < 0 else "1.4 is the same as 1.5 (0)"
+        lambda x: f"1.5 is stronger than 1.4 ({x:.8f})" if x < 0 else (
+            f"1.4 is stronger than 1.5 ({-x:.8f})" if x > 0 else "1.4 is the same as 1.5 (0)"
         )
     )
     
     merged_df["CharacterErrorRate_Comparison"] = merged_df["CharacterErrorRate_Diff"].apply(
-        lambda x: f"1.5 is stronger than 1.4 ({x:.8f})" if x > 0 else (
-            f"1.4 is stronger than 1.5 ({-x:.8f})" if x < 0 else "1.4 is the same as 1.5 (0)"
+        lambda x: f"1.5 is stronger than 1.4 ({x:.8f})" if x < 0 else (
+            f"1.4 is stronger than 1.5 ({-x:.8f})" if x > 0 else "1.4 is the same as 1.5 (0)"
         )
     )
     
-    def overall_comparison(row):
-        word_diff = row["WordErrorRate_Diff"]
-        char_diff = row["CharacterErrorRate_Diff"]
-        if word_diff > 0 and char_diff > 0:
-            return "1.5 is overall stronger than 1.4"
-        elif word_diff < 0 and char_diff < 0:
-            return "1.4 is overall stronger than 1.5"
-        elif word_diff == 0 and char_diff == 0:
-            return "1.4 is the same as 1.5 overall"
-        else:
-            return "Mixed results: check individual metrics"
-    
-    merged_df["Overall_Comparison"] = merged_df.apply(overall_comparison, axis=1)
-    
     result = merged_df[[
         "SourceText",
         "WordErrorRate_1.5", "WordErrorRate_1.4", "WordErrorRate_Comparison",
-        "CharacterErrorRate_1.5", "CharacterErrorRate_1.4", "CharacterErrorRate_Comparison",
-        "Overall_Comparison"
+        "CharacterErrorRate_1.5", "CharacterErrorRate_1.4", "CharacterErrorRate_Comparison"
     ]]
     
     return result.to_html(index=False)