fix rounding

app.py

@@ -26,6 +26,7 @@ def filter_dfs(tags, lb):
         lb = f_b_df.copy()
     if tags and len(lb) > 0:
         lb = lb[lb["Tags"].apply(lambda x: any(tag in x for tag in tags))]
+    lb = rounded_df(lb)
     return lb
 
 def change_mean(env, lb):
@@ -36,6 +37,7 @@ def change_mean(env, lb):
     else:
         mean_cols = [col for col in lb.columns if str(col) not in ["Mean", "Model", "Tags"]]
     lb["Mean"] = lb[mean_cols].mean(axis=1)
+    lb = rounded_df(lb)
     return lb
 
 def restart_space():
@@ -132,6 +134,13 @@ except Exception:
     restart_space()
 
 
+def rounded_df(df):
+    df = df.copy()
+    for col in df.columns:
+        if isinstance(col.values[0], float):
+            df[col] = df[col].apply(lambda x: round(x, 2))
+    return df
+
 results_df = pd.read_csv(EVAL_RESULTS_PATH + "/results.csv")
 
 agg_df = BenchmarkSuite.aggregate_df(results_df)
@@ -142,8 +151,6 @@ mean_cols = [col for col in agg_df.columns if str(col) not in ["Mean", "Environm
 agg_df["Mean"] = agg_df[mean_cols].mean(axis=1)
 # make sure mean is the first column
 agg_df = agg_df[["Mean"] + [col for col in agg_df.columns if col != "Mean"]]
-for col in agg_df.columns:
-    agg_df[col] = agg_df[col].apply(lambda x: round(x, 2))
 agg_df["Tags"] = ""
 agg_df.reset_index(inplace=True)
 agg_df.rename(columns={"dataset": "Model"}, inplace=True)
@@ -161,9 +168,6 @@ benchmark_df.set_index("Model", inplace=True)
 benchmark_df["Mean"] = benchmark_df.mean(axis=1)
 # make sure mean is the first column
 benchmark_df = benchmark_df[["Mean"] + [col for col in benchmark_df.columns if col != "Mean"]]
-# round all
-for col in benchmark_df.columns:
-    benchmark_df[col] = benchmark_df[col].apply(lambda x: round(x, 2))
 benchmark_df["Tags"] = ""
 benchmark_df.reset_index(inplace=True)
 benchmark_df.sort_values("Mean", ascending=False, inplace=True)
@@ -204,7 +208,7 @@ def init_leaderboard(dataframe):
     cols = list(dataframe.columns)
     cols.remove("Tags")
     return Leaderboard(
-        value=dataframe,
+        value=rounded_df(dataframe),
         select_columns=SelectColumns(
             default_selection=cols,
             cant_deselect=["Model", "Mean"],