Log df shape

src/populate.py

@@ -44,10 +44,11 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
 
     # # filter out if any of the benchmarks have not been produced
     # df = df[has_no_nan_values(df, benchmark_cols)]
+    df = df.fillna("-")
 
     # make values clickable and link to log files
     for col in benchmark_cols:
-        df[col] = df[[AutoEvalColumn.model.name, col]].apply(lambda x: f"[{x[col]}]({get_inspect_log_url(model_name=x[AutoEvalColumn.model.name].split('>')[1].split('<')[0], benchmark_name=TASK_NAME_INVERSE_MAP[col]['name'])})" if x[col] != np.nan else "-", axis=1)
+        df[col] = df[[AutoEvalColumn.model.name, col]].apply(lambda x: f"[{x[col]}]({get_inspect_log_url(model_name=x[AutoEvalColumn.model.name].split('>')[1].split('<')[0], benchmark_name=TASK_NAME_INVERSE_MAP[col]['name'])})" if x[col] != "-" else x[col], axis=1)
 
     # # make task names clickable and link to inspect-evals repository - this creates issues later
     # df = df.rename(columns={col: f"[{col}]({TASK_NAME_INVERSE_MAP[col]['source']})" for col in benchmark_cols})