Update app.py

app.py

@@ -82,9 +82,16 @@ def generate_mock_historical_data(num_teams, num_conferences, num_inter_games, s
 
 # Team Workload Analysis
 def team_workload_analysis(schedule_df):
+    # Check if the DataFrame is None
     if schedule_df is None:
+        plt.figure(figsize=(10, 6))
+        plt.text(0.5, 0.5, 'Please generate the schedule first before viewing analytics.', 
+                 horizontalalignment='center', verticalalignment='center', 
+                 fontsize=14, color='red')
+        plt.axis('off')
+        plt.tight_layout()
+        plt.show()
         return
-    else
     """Generate a bar chart showing the number of matches each team has per week."""
     schedule_df['Week'] = schedule_df['Date'].dt.isocalendar().week
     team_counts = schedule_df.groupby(['Week', 'Team 1']).size().unstack().fillna(0)
@@ -100,9 +107,16 @@ def team_workload_analysis(schedule_df):
 
 # Match Distribution
 def match_distribution(schedule_df):
+    # Check if the DataFrame is None
     if schedule_df is None:
+        plt.figure(figsize=(10, 6))
+        plt.text(0.5, 0.5, 'Please generate the schedule first before viewing analytics.', 
+                 horizontalalignment='center', verticalalignment='center', 
+                 fontsize=14, color='red')
+        plt.axis('off')
+        plt.tight_layout()
+        plt.show()
         return
-    else
     """Generate a histogram showing match distribution across months."""
     schedule_df['Month'] = schedule_df['Date'].dt.month_name()
     month_order = ['November', 'December', 'January', 'February', 'March']
@@ -118,9 +132,16 @@ def match_distribution(schedule_df):
 
 # Inter-Conference Match Analysis
 def inter_conference_analysis(schedule_df):
+    # Check if the DataFrame is None
     if schedule_df is None:
+        plt.figure(figsize=(10, 6))
+        plt.text(0.5, 0.5, 'Please generate the schedule first before viewing analytics.', 
+                 horizontalalignment='center', verticalalignment='center', 
+                 fontsize=14, color='red')
+        plt.axis('off')
+        plt.tight_layout()
+        plt.show()
         return
-    else
     """Generate a heatmap showing inter-conference match frequencies."""
     # Extract the conference from the team names
     schedule_df['Conference 1'] = schedule_df['Team 1'].str[0]
@@ -152,9 +173,16 @@ def inter_conference_analysis(schedule_df):
 
 # Commissioner Analytics
 def commissioner_analytics(schedule_df, commissioners):
+    # Check if the DataFrame is None
     if schedule_df is None:
+        plt.figure(figsize=(10, 6))
+        plt.text(0.5, 0.5, 'Please generate the schedule first before viewing analytics.', 
+                 horizontalalignment='center', verticalalignment='center', 
+                 fontsize=14, color='red')
+        plt.axis('off')
+        plt.tight_layout()
+        plt.show()
         return
-    else
     """Generate a bar chart showing matches overseen by each commissioner."""
     # Assuming each commissioner oversees a specific conference
     comm_dict = {f"Conference {chr(65+i)}": comm for i, comm in enumerate(commissioners)}