Add explicit column names. Update requirements.

requirements.txt

@@ -9,7 +9,7 @@ gradio_client
 huggingface-hub>=0.18.0
 matplotlib
 numpy<2.0.0
-pandas
+pandas>=2.0.0
 python-dateutil
 tqdm
 transformers

src/populate.py

@@ -47,12 +47,25 @@ def get_tossups_leaderboard_df(repo_dir: str, eval_split: str) -> pd.DataFrame:
             if "human_win_rate" in metrics:
                 row["Win Rate w/ Humans"] = metrics["human_win_rate"]
                 row["Win Rate w/ Humans (Aggressive)"] = metrics["human_win_rate_strict"]
+            else:
+                row["Win Rate w/ Humans"] = None
+                row["Win Rate w/ Humans (Aggressive)"] = None
             eval_results.append(row)
         except Exception as e:
             logger.error(f"Error processing model result '{username}/{model_name}': {e}")
             continue
 
-    return pd.DataFrame(eval_results)
+    return pd.DataFrame(
+        eval_results,
+        columns=[
+            "Submission",
+            "Avg Score ⬆️",
+            "Buzz Accuracy",
+            "Buzz Position",
+            "Win Rate w/ Humans",
+            "Win Rate w/ Humans (Aggressive)",
+        ],
+    )
 
 
 def get_bonuses_leaderboard_df(repo_dir: str, eval_split: str) -> pd.DataFrame:
@@ -75,7 +88,10 @@ def get_bonuses_leaderboard_df(repo_dir: str, eval_split: str) -> pd.DataFrame:
             logger.error(f"Error processing model result '{username}/{model_name}': {e}")
             continue
 
-    return pd.DataFrame(eval_results)
+    return pd.DataFrame(
+        eval_results,
+        columns=["Submission", "Question Accuracy", "Part Accuracy"],
+    )
 
 
 def get_evaluation_queue_df(save_path: str, cols: list) -> list[pd.DataFrame]: