Update app.py

app.py

@@ -398,22 +398,54 @@ class VisualizationEngine:
         return fig
     
     @staticmethod
-    def create_revenue_trend(df: pd.DataFrame):
-        """Create revenue trend visualization"""
+    def create_revenue_trend(df: pd.DataFrame, time_granularity='month', customer_filter='all'):
+        """Create revenue trend visualization with filters"""
         df_copy = df.copy()
-        df_copy['order_month'] = df_copy['order_date'].dt.to_period('M')
-        monthly_revenue = df_copy.groupby('order_month')['amount'].sum().reset_index()
-        monthly_revenue['order_month'] = monthly_revenue['order_month'].astype(str)
+        
+        # Filter by customer if specified
+        if customer_filter != 'all' and customer_filter:
+            df_copy = df_copy[df_copy['customer_id'] == customer_filter]
+            if df_copy.empty:
+                # Return empty chart with message
+                fig = go.Figure()
+                fig.add_annotation(text=f"No data found for customer {customer_filter}", 
+                                 xref="paper", yref="paper", x=0.5, y=0.5, showarrow=False)
+                fig.update_layout(title=f"Revenue Trend - {customer_filter}", height=400)
+                return fig
+        
+        # Group by time granularity
+        if time_granularity == 'day':
+            df_copy['time_period'] = df_copy['order_date'].dt.date
+            title_suffix = "Daily"
+        elif time_granularity == 'week':
+            df_copy['time_period'] = df_copy['order_date'].dt.to_period('W')
+            title_suffix = "Weekly"
+        elif time_granularity == 'year':
+            df_copy['time_period'] = df_copy['order_date'].dt.to_period('Y')
+            title_suffix = "Yearly"
+        else:  # default to month
+            df_copy['time_period'] = df_copy['order_date'].dt.to_period('M')
+            title_suffix = "Monthly"
+        
+        revenue_data = df_copy.groupby('time_period')['amount'].sum().reset_index()
+        revenue_data['time_period'] = revenue_data['time_period'].astype(str)
+        
+        # Create title
+        if customer_filter == 'all':
+            title = f"{title_suffix} Revenue Trends - All Customers"
+        else:
+            title = f"{title_suffix} Revenue Trends - {customer_filter}"
         
         fig = px.line(
-            monthly_revenue, 
-            x='order_month', 
+            revenue_data, 
+            x='time_period', 
             y='amount',
-            title='Monthly Revenue Trends',
-            labels={'amount': 'Revenue ($)', 'order_month': 'Month'}
+            title=title,
+            labels={'amount': 'Revenue ($)', 'time_period': 'Time Period'}
         )
         fig.update_traces(line_color=COLORS['primary'], line_width=3)
         fig.update_layout(height=400, title={'x': 0.5, 'xanchor': 'center'})
+        
         return fig
     
     @staticmethod
@@ -582,6 +614,21 @@ class B2BCustomerAnalytics:
         
         return segment_chart, rfm_chart, churn_chart, revenue_chart
     
+    def get_revenue_chart_with_filters(self, time_granularity='month', customer_filter='all'):
+        """Get revenue chart with time and customer filters"""
+        if self.raw_data is None:
+            return None
+        
+        return VisualizationEngine.create_revenue_trend(
+            self.raw_data, time_granularity, customer_filter
+        )
+    
+    def get_customer_list(self):
+        """Get list of customer IDs for dropdown"""
+        if self.raw_data is None:
+            return []
+        return ['all'] + sorted(self.raw_data['customer_id'].unique().tolist())
+    
     def get_customer_table(self) -> Optional[pd.DataFrame]:
         """Get formatted customer table"""
         if self.customer_metrics is None:
@@ -800,6 +847,22 @@ class B2BCustomerAnalytics:
         
         return " • ".join(recommendations) if recommendations else "Continue monitoring customer engagement patterns."
 
+def update_revenue_chart(analytics_instance, time_gran, customer_id):
+    """Update revenue chart based on filters"""
+    try:
+        chart = analytics_instance.get_revenue_chart_with_filters(time_gran, customer_id)
+        return chart
+    except Exception as e:
+        return None
+
+def update_customer_dropdown(analytics_instance):
+    """Update customer dropdown options"""
+    try:
+        customers = analytics_instance.get_customer_list()
+        return gr.Dropdown(choices=customers, value='all')
+    except:
+        return gr.Dropdown(choices=['all'], value='all')
+
 def create_gradio_interface():
     """Create the enhanced Gradio interface"""
     
@@ -832,7 +895,7 @@ def create_gradio_interface():
         
         with gr.Tabs():
             
-            with gr.Tab("📊 Data Upload & Dashboard"):
+            with gr.Tab("Data Upload & Dashboard"):
                 with gr.Row():
                     with gr.Column():
                         file_input = gr.File(
@@ -854,7 +917,7 @@ def create_gradio_interface():
                 summary_display = gr.HTML()
                 data_preview = gr.DataFrame(label="Data Preview (First 20 Rows)")
             
-            with gr.Tab("🎯 Customer Segmentation"):
+            with gr.Tab("Customer Segmentation"):
                 with gr.Row():
                     with gr.Column():
                         segment_chart = gr.Plot(label="Customer Segments Distribution")
@@ -875,7 +938,7 @@ def create_gradio_interface():
                 </div>
                 """)
             
-            with gr.Tab("🤖 Churn Prediction"):
+            with gr.Tab("Churn Prediction"):
                 train_btn = gr.Button(
                     "Train Churn Prediction Model", 
                     variant="primary", 
@@ -899,19 +962,36 @@ def create_gradio_interface():
                 </div>
                 """)
             
-            with gr.Tab("📈 Revenue Analytics"):
-                revenue_chart = gr.Plot(label="Monthly Revenue Trends")
+            with gr.Tab("Revenue Analytics"):
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        time_granularity = gr.Radio(
+                            choices=['day', 'week', 'month', 'year'],
+                            value='month',
+                            label="Time Granularity"
+                        )
+                        customer_filter = gr.Dropdown(
+                            choices=[],  # Will be populated dynamically
+                            value='all',
+                            label="Customer Filter"
+                        )
+                        update_chart_btn = gr.Button("Update Chart", variant="primary")
+                    
+                    with gr.Column(scale=3):
+                        revenue_chart = gr.Plot(label="Revenue Trends")
                 
+                # Add the info box
                 gr.HTML("""
                 <div style="background: #ecfdf5; padding: 1rem; border-radius: 8px; border-left: 4px solid #10b981; margin-top: 1rem;">
-                    <h4 style="color: #065f46; margin: 0 0 0.5rem 0;">Revenue Insights</h4>
+                    <h4 style="color: #065f46; margin: 0 0 0.5rem 0;">Interactive Revenue Analysis</h4>
                     <p style="margin: 0; color: #1f2937; font-size: 0.9rem;">
-                        Track revenue trends over time to identify seasonal patterns, growth trajectories, and potential business impact of customer segments.
+                        Select time granularity (day/week/month/year) and specific customers to analyze revenue patterns. 
+                        Use "all" to view aggregate trends across all customers.
                     </p>
                 </div>
                 """)
             
-            with gr.Tab("👤 Customer Insights"):
+            with gr.Tab("Customer Insights"):
                 with gr.Row():
                     customer_id_input = gr.Textbox(
                         label="Customer ID", 
@@ -926,7 +1006,7 @@ def create_gradio_interface():
                 
                 customer_insights = gr.HTML()
             
-            with gr.Tab("📋 Reports"):
+            with gr.Tab("Reports"):
                 with gr.Row():
                     with gr.Column():
                         gr.HTML("""
@@ -953,20 +1033,23 @@ def create_gradio_interface():
         def safe_load_data(analytics_instance, file):
             try:
                 if file is None:
-                    return analytics_instance, "Please upload a CSV file", "", None, None, None, None, None, None
+                    return analytics_instance, "Please upload a CSV file", "", None, None, None, None, None, None, gr.Dropdown(choices=['all'], value='all')
                 
                 status, dashboard, preview = analytics_instance.load_data(file)
                 
                 if "successfully" in status:
                     charts = analytics_instance.get_visualizations()
                     table = analytics_instance.get_customer_table()
-                    return analytics_instance, status, dashboard, preview, *charts, table
+                    # Update customer dropdown
+                    customers = analytics_instance.get_customer_list()
+                    customer_dropdown = gr.Dropdown(choices=customers, value='all')
+                    return analytics_instance, status, dashboard, preview, *charts, table, customer_dropdown
                 else:
-                    return analytics_instance, status, "", None, None, None, None, None, None
+                    return analytics_instance, status, "", None, None, None, None, None, None, gr.Dropdown(choices=['all'], value='all')
                     
             except Exception as e:
                 error_msg = f"Error loading data: {str(e)}"
-                return analytics_instance, error_msg, "", None, None, None, None, None, None
+                return analytics_instance, error_msg, "", None, None, None, None, None, None, gr.Dropdown(choices=['all'], value='all')
         
         def safe_train_model(analytics_instance):
             try:
@@ -1006,7 +1089,27 @@ def create_gradio_interface():
             fn=safe_load_data,
             inputs=[analytics, file_input],
             outputs=[analytics, load_status, summary_display, data_preview, 
-                    segment_chart, rfm_chart, churn_distribution_chart, revenue_chart, customer_table]
+                    segment_chart, rfm_chart, churn_distribution_chart, revenue_chart, customer_table, customer_filter]
+        )
+        
+        # Update chart when filters change
+        update_chart_btn.click(
+            fn=update_revenue_chart,
+            inputs=[analytics, time_granularity, customer_filter],
+            outputs=[revenue_chart]
+        )
+        
+        # Auto-update on filter change
+        time_granularity.change(
+            fn=update_revenue_chart,
+            inputs=[analytics, time_granularity, customer_filter],
+            outputs=[revenue_chart]
+        )
+        
+        customer_filter.change(
+            fn=update_revenue_chart,
+            inputs=[analytics, time_granularity, customer_filter],
+            outputs=[revenue_chart]
         )
         
         train_btn.click(