added info on unique users

app.py

@@ -160,13 +160,13 @@ def update_data_per_env(rl_env):
 
 
 
-def get_info_display(len_dataframe,env_name,name_leaderboard,is_empty):
+def get_info_display(dataframe,env_name,name_leaderboard,is_empty):
     if not is_empty:
         markdown = """
         <div class='infoPoint'>
         <h1> {name_leaderboard} </h1>
         <br>
-        <p> This is a leaderboard of <b>{len_dataframe}</b> agents playing {env_name} 👩‍🚀. </p>
+        <p> This is a leaderboard of <b>{len_dataframe}</b> agents, from <b>{num_unique_users}</b> unique users, playing {env_name} 👩‍🚀. </p>
         <br>
         <p> We use lower bound result to sort the models: mean_reward - std_reward. </p>
         <br>    
@@ -175,7 +175,7 @@ def get_info_display(len_dataframe,env_name,name_leaderboard,is_empty):
         <p> You want to try your model? Read this <a href="https://github.com/huggingface/deep-rl-class/blob/Unit1/unit1/README.md" target="_blank">Unit 1</a> of Deep Reinforcement Learning Class.
         </p>
         </div>
-        """.format(len_dataframe = len_dataframe,env_name = env_name,name_leaderboard = name_leaderboard)
+        """.format(len_dataframe = len(dataframe),env_name = env_name,name_leaderboard = name_leaderboard,num_unique_users = len(set(dataframe['User'].values)))
 
     else:
         markdown = """
@@ -205,7 +205,7 @@ def reload_leaderboard(rl_env):
  
     data_html,data_dataframe,is_empty = RL_DETAILS[rl_env]['data'] 
 
-    markdown = get_info_display(len(data_dataframe),rl_env,RL_DETAILS[rl_env]['title'],is_empty)            
+    markdown = get_info_display(data_dataframe,rl_env,RL_DETAILS[rl_env]['title'],is_empty)            
     
     return markdown,data_html     
             
@@ -226,7 +226,7 @@ with block:
         for rl_env in RL_ENVS:
             with gr.TabItem(rl_env) as rl_tab:
                 data_html,data_dataframe,is_empty = RL_DETAILS[rl_env]['data'] 
-                markdown = get_info_display(len(data_dataframe),rl_env,RL_DETAILS[rl_env]['title'],is_empty)            
+                markdown = get_info_display(data_dataframe,rl_env,RL_DETAILS[rl_env]['title'],is_empty)            
                 env_state =gr.Variable(default_value=rl_env)  
                 output_markdown = gr.HTML(markdown)
                 reload = gr.Button('Reload Leaderboard')