rank

src/populate.py

@@ -18,8 +18,9 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
     df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
     df = df[cols].round(decimals=2)
 
-    # add column rank to pd.DataFrame df
-    df.insert(0, "rank", df[AutoEvalColumn.average.name].rank(ascending=False, method="min"), True)
+    # set column rank to pd.DataFrame df
+    df['rank'] = df[AutoEvalColumn.average.name].rank(ascending=False, method="min")
+    # df.insert(0, "rank", df[AutoEvalColumn.average.name].rank(ascending=False, method="min"), True)
 
     # filter out if any of the benchmarks have not been produced
     #df2 = df[has_no_nan_values(df, benchmark_cols)]