Adding fix

app.py

@@ -266,56 +266,56 @@ def display_predictions():
             st.write("No predictions for today's matches yet.")
 
 
-# def display_leaderboard():
-#     if st.button("Show Leaderboard"):
-#         try:
-#             users = load_users(USERS_JSON)
-#             # Convert the dataset to a pandas DataFrame
-#             df_users = pd.DataFrame([{'User': key, 'Points': value} for key, value in users.items()])
+def display_leaderboard():
+    if st.button("Show Leaderboard"):
+        try:
+            users = load_users(USERS_JSON)
+            # Convert the dataset to a pandas DataFrame
+            df_users = pd.DataFrame([{'User': key, 'Points': value} for key, value in users.items()])
 
-#             # Sort DataFrame by points in descending order
-#             leaderboard = df_users.sort_values(by='Points', ascending=False).reset_index(drop=True)
+            # Sort DataFrame by points in descending order
+            leaderboard = df_users.sort_values(by='Points', ascending=False).reset_index(drop=True)
             
-#             # Add a 'Rank' column starting from 1
-#             leaderboard['Rank'] = leaderboard.index + 1
+            # Add a 'Rank' column starting from 1
+            leaderboard['Rank'] = leaderboard.index + 1
             
-#             # Reorder DataFrame columns so 'Rank' is first
-#             df_leaderboard = leaderboard[['Rank', 'User', 'Points']]
+            # Reorder DataFrame columns so 'Rank' is first
+            df_leaderboard = leaderboard[['Rank', 'User', 'Points']]
             
-#             st.dataframe(df_leaderboard, hide_index=True)
-#         except FileNotFoundError:
-#             st.write("Leaderboard data not available.")
+            st.dataframe(df_leaderboard, hide_index=True)
+        except FileNotFoundError:
+            st.write("Leaderboard data not available.")
 
 
-def display_leaderboard():
-    if st.button("Show Leaderboard"):
-        try:
-            # Load the 'leaders' configuration or split from your dataset
-            dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
-            # Convert the dataset to a pandas DataFrame
-            df_users = pd.DataFrame(dataset)
+# def display_leaderboard():
+#     if st.button("Show Leaderboard"):
+#         try:
+#             # Load the 'leaders' configuration or split from your dataset
+#             dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
+#             # Convert the dataset to a pandas DataFrame
+#             df_users = pd.DataFrame(dataset)
             
-            # Transform the DataFrame to have 'user_name' and 'points' columns
-            # Since your JSON structure is quite unique, this step may need adjustment based on how the DataFrame is loaded
-            users_data = []
-            for column in df_users.columns:
-                points = df_users[column].iloc[0]  # Assuming the first (and only) row contains the points for each user
-                users_data.append({'User': column, 'Points': points})
-
-            df_leaderboard = pd.DataFrame(users_data)
+#             # Transform the DataFrame to have 'user_name' and 'points' columns
+#             # Since your JSON structure is quite unique, this step may need adjustment based on how the DataFrame is loaded
+#             users_data = []
+#             for column in df_users.columns:
+#                 points = df_users[column].iloc[0]  # Assuming the first (and only) row contains the points for each user
+#                 users_data.append({'User': column, 'Points': points})
+
+#             df_leaderboard = pd.DataFrame(users_data)
             
-            # Sort DataFrame by points in descending order
-            df_leaderboard = df_leaderboard.sort_values(by='Points', ascending=False)
+#             # Sort DataFrame by points in descending order
+#             df_leaderboard = df_leaderboard.sort_values(by='Points', ascending=False)
             
-            # Add a 'Rank' column starting from 1
-            df_leaderboard['Rank'] = range(1, len(df_leaderboard) + 1)
+#             # Add a 'Rank' column starting from 1
+#             df_leaderboard['Rank'] = range(1, len(df_leaderboard) + 1)
             
-            # Select and order the columns for display
-            df_leaderboard = df_leaderboard[['Rank', 'User', 'Points']]
+#             # Select and order the columns for display
+#             df_leaderboard = df_leaderboard[['Rank', 'User', 'Points']]
             
-            st.dataframe(df_leaderboard, hide_index=True)
-        except Exception as e:
-            st.write("Failed to load leaderboard data: ", str(e))
+#             st.dataframe(df_leaderboard, hide_index=True)
+#         except Exception as e:
+#             st.write("Failed to load leaderboard data: ", str(e))
 
 
 # Streamlit UI

leaders/users.json

@@ -1,17 +1,17 @@
 {
     "Arpit": 10100,
     "Ganesh": 8151,
-    "Haaris": 13600,
-    "Jay": 8400,
-    "Kishore": 9400,
-    "Megha": 9150,
-    "Naveein": 10600,
-    "Neha": 7800,
-    "Praveen": 15100,
-    "Rakesh": 8500,
-    "Sai": 6820,
-    "Sahil": 9950,
-    "Sunil": 7361,
-    "Vaibhav": 7199,
-    "Vinay": 8250
+    "Haaris": 15100,
+    "Jay": 7700,
+    "Kishore": 8700,
+    "Megha": 11250,
+    "Naveein": 8000,
+    "Neha": 7600,
+    "Praveen": 17100,
+    "Rakesh": 7300,
+    "Sai": 9984,
+    "Sahil": 9550,
+    "Sunil": 7689,
+    "Vaibhav": 7999,
+    "Vinay": 7900
 }

match_outcomes.json

@@ -48,5 +48,20 @@
         "match_id": "20240329_10",
         "winning_team": "KKR",
         "man_of_the_match": "Sunil Narine"
+    },
+    {
+        "match_id": "20240330_11",
+        "winning_team": "LSG",
+        "man_of_the_match": "Mayank Yadav"
+    },
+    {
+        "match_id": "20240331_12",
+        "winning_team": "GT",
+        "man_of_the_match": "Mohit Sharma"
+    },
+    {
+        "match_id": "20240331_13",
+        "winning_team": "DC",
+        "man_of_the_match": "Khaleel Ahmed"
     }
 ]

users.json

@@ -1,17 +1,17 @@
 {
     "Arpit": 10100,
     "Ganesh": 8151,
-    "Haaris": 13600,
-    "Jay": 8400,
-    "Kishore": 9400,
-    "Megha": 9150,
-    "Naveein": 10600,
-    "Neha": 7800,
-    "Praveen": 15100,
-    "Rakesh": 8500,
-    "Sai": 6820,
-    "Sahil": 9950,
-    "Sunil": 7361,
-    "Vaibhav": 7199,
-    "Vinay": 8250
+    "Haaris": 15100,
+    "Jay": 7700,
+    "Kishore": 8700,
+    "Megha": 11250,
+    "Naveein": 8000,
+    "Neha": 7600,
+    "Praveen": 17100,
+    "Rakesh": 7300,
+    "Sai": 9984,
+    "Sahil": 9550,
+    "Sunil": 7689,
+    "Vaibhav": 7999,
+    "Vinay": 7900
 }