fix missing import in eval outlier

mu_map/random_search/eval/outlier.py

+import pandas as pd
+
 from mu_map.random_search.eval.params import parameter_groups
 from mu_map.random_search.eval.util import filter_by_params, load_data, remove_outliers
 
@@ -11,16 +13,21 @@ outlier_runs = list(outlier_runs["run"])
 data_outlier = dict(filter(lambda i: i[0] in outlier_runs, data.items()))
 n_outlier = len(data_outlier)
 
-print(f"There are {n_outlier} outlier runs in {n_total} total runs which is {100 * n_outlier / n_total:.2f}%")
+print(
+    f"There are {n_outlier} outlier runs in {n_total} total runs which is {100 * n_outlier / n_total:.2f}%"
+)
 print()
 print(f"By Parameters:")
 for param_label, param_groups in parameter_groups.items():
-    param_label = " ".join(map(lambda _str: _str[0].upper() + _str[1:], param_label.split("_")))
+    param_label = " ".join(
+        map(lambda _str: _str[0].upper() + _str[1:], param_label.split("_"))
+    )
     print(f" - {param_label}")
 
     for label, value in param_groups.groups.items():
         n_outlier = len(filter_by_params(data_outlier, value, param_groups.keys))
         n_total = len(filter_by_params(data, value, param_groups.keys))
-        print(f"   - {label:>12}: {str(n_outlier):>2}/{str(n_total):>2} = {100 * n_outlier / n_total:.2f}%")
+        print(
+            f"   - {label:>12}: {str(n_outlier):>2}/{str(n_total):>2} = {100 * n_outlier / n_total:.2f}%"
+        )
     print()
-