diff --git a/predicators/envs/sticky_table.py b/predicators/envs/sticky_table.py
index d5ed4d6a96..f68ddaadb9 100644
--- a/predicators/envs/sticky_table.py
+++ b/predicators/envs/sticky_table.py
@@ -379,7 +379,7 @@ def _get_tasks(self, num: int,
                     "sticky": sticky
                 }
             tables = sorted(state_dict)
-            # rng.shuffle(tables)  # type: ignore
+            rng.shuffle(tables)  # type: ignore
             target_table = tables[-1]
             cube_table, cup_table  = tables[:2]
             # Create cube.
diff --git a/scripts/plotting/create_active_sampler_learning_plots.py b/scripts/plotting/create_active_sampler_learning_plots.py
index d490f523e2..e8a871a43f 100644
--- a/scripts/plotting/create_active_sampler_learning_plots.py
+++ b/scripts/plotting/create_active_sampler_learning_plots.py
@@ -126,8 +126,8 @@ def _derive_per_task_average(metric: str,
             lambda v: "sticky_table-success_rate_explore" in v)),
         ("Task-Relevant", "purple", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "sticky_table-random_score_explore" in v)),
-        ("Random Skills", "blue", lambda df: df["EXPERIMENT_ID"].apply(
-            lambda v: "sticky_table-random_nsrts_explore" in v)),
+        # ("Random Skills", "blue", lambda df: df["EXPERIMENT_ID"].apply(
+        #     lambda v: "sticky_table-random_nsrts_explore" in v)),
         # ("Maple Q", "gray", lambda df: df["EXPERIMENT_ID"].apply(
         #     lambda v: "sticky_table-maple_q" in v)),
     ],