Update app.py

app.py

@@ -20,8 +20,8 @@ def upload_csv(file):
         if df.empty:
             return ["All"], ["All"], ["All"], "The uploaded CSV file is empty.", "All", "All", "All"
         
-        # Define required columns
-        required_columns = {'DeviceID', 'Lab', 'Type', 'Timestamp', 'Status', 'UsageCount', 'Health'}
+        # Define required columns (removed 'Health')
+        required_columns = {'DeviceID', 'Lab', 'Type', 'Timestamp', 'Status', 'UsageCount'}
         if not required_columns.issubset(df.columns):
             missing_cols = required_columns - set(df.columns)
             return ["All"], ["All"], ["All"], f"CSV is missing required columns: {', '.join(missing_cols)}", "All", "All", "All"
@@ -62,8 +62,8 @@ def filter_and_visualize(selected_lab, selected_type, selected_date_range):
     if filtered_df.empty:
         return None, None, None, None, "No data matches the selected filters."
     
-    # Device Cards (as a table)
-    device_cards = filtered_df[['DeviceID', 'Lab', 'Type', 'Health', 'UsageCount', 'Timestamp']].sort_values(by='Timestamp', ascending=False)
+    # Device Cards (as a table, removed 'Health')
+    device_cards = filtered_df[['DeviceID', 'Lab', 'Type', 'UsageCount', 'Timestamp']].sort_values(by='Timestamp', ascending=False)
     
     # Daily Log Trends (Line Chart)
     daily_logs = filtered_df.groupby(filtered_df['Timestamp'].dt.date).size()
@@ -128,9 +128,9 @@ def download_pdf(selected_lab, selected_type, selected_date_range):
     pdf.cell(200, 10, txt="LabOps Dashboard Report", ln=True, align='C')
     pdf.ln(10)
     
-    # Add filtered data
+    # Add filtered data (removed 'Health')
     for index, row in filtered_df.iterrows():
-        line = f"{row['Timestamp']} | {row['DeviceID']} | {row['Lab']} | {row['Type']} | {row['Status']} | {row['UsageCount']} | {row['Health']}"
+        line = f"{row['Timestamp']} | {row['DeviceID']} | {row['Lab']} | {row['Type']} | {row['Status']} | {row['UsageCount']}"
         pdf.multi_cell(0, 10, txt=line)
     
     output = io.BytesIO()
@@ -151,7 +151,7 @@ with gr.Blocks() as demo:
         date_dropdown = gr.Dropdown(label="Filter by Date Range", choices=["All"], value="All")
 
     with gr.Row():
-        device_table = gr.DataFrame(label="Device Cards (Health, Usage, Last Log)")
+        device_table = gr.DataFrame(label="Device Cards (Usage, Last Log)")
         plot_daily = gr.Image(label="Daily Log Trends")
         plot_uptime = gr.Image(label="Weekly Uptime %")