update dashboard.py - overlap issue

app.py

@@ -234,8 +234,8 @@ def create_interface():
         theme=gr.themes.Soft(),
         css="""
         footer {visibility: hidden}
-        .plot-container {min-height: 950px !important}
-        .gradio-plot {min-height: 950px !important}
+        .plot-container {min-height: 1150px !important}
+        .gradio-plot {min-height: 1150px !important}
         """
     ) as demo:
         

dashboard.py

@@ -28,19 +28,19 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
     if sales_data.empty:
         return create_empty_chart("No sales data available")
     
-    # Create subplot layout
+    # Create subplot layout with better spacing
     fig = make_subplots(
-        rows=2, cols=2,
+        rows=3, cols=1,
         subplot_titles=[
             "📈 Daily Revenue Trend",
-            "🏆 Top Products by Revenue", 
-            "📊 Sales by Category",
-            "💰 Revenue Distribution"
+            "🏆 Top Products by Revenue",
+            "📊 Sales by Category"
         ],
-        specs=[[{"secondary_y": True}, {"type": "bar"}],
-               [{"type": "pie"}, {"type": "histogram"}]],
-        vertical_spacing=0.20,
-        horizontal_spacing=0.15
+        specs=[[{"secondary_y": True}],
+               [{"type": "bar"}],
+               [{"type": "pie"}]],
+        vertical_spacing=0.15,
+        row_heights=[0.4, 0.35, 0.25]
     )
     
     try:
@@ -78,9 +78,9 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
                 row=1, col=1, secondary_y=True
             )
         
-        # 2. Top Products by Revenue (Top Right)
+        # 2. Top Products by Revenue (Second Row)
         if 'product_name' in sales_data.columns and 'total_price' in sales_data.columns:
-            top_products = sales_data.groupby('product_name')['total_price'].sum().nlargest(10).reset_index()
+            top_products = sales_data.groupby('product_name')['total_price'].sum().nlargest(8).reset_index()
             
             fig.add_trace(
                 go.Bar(
@@ -91,10 +91,10 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
                     marker_color='#A23B72',
                     hovertemplate='<b>%{y}</b><br>Revenue: ₽%{x:,.0f}<extra></extra>'
                 ),
-                row=1, col=2
+                row=2, col=1
             )
         
-        # 3. Sales by Category (Bottom Left)
+        # 3. Sales by Category (Third Row)
         if 'category' in sales_data.columns and 'total_price' in sales_data.columns:
             category_sales = sales_data.groupby('category')['total_price'].sum().reset_index()
             
@@ -106,20 +106,7 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
                     hovertemplate='<b>%{label}</b><br>Revenue: ₽%{value:,.0f}<br>Percent: %{percent}<extra></extra>',
                     marker_colors=px.colors.qualitative.Set3
                 ),
-                row=2, col=1
-            )
-        
-        # 4. Revenue Distribution (Bottom Right)
-        if 'total_price' in sales_data.columns:
-            fig.add_trace(
-                go.Histogram(
-                    x=sales_data['total_price'],
-                    nbinsx=20,
-                    name='Revenue Distribution',
-                    marker_color='#F18F01',
-                    hovertemplate='Range: ₽%{x}<br>Count: %{y}<extra></extra>'
-                ),
-                row=2, col=2
+                row=3, col=1
             )
     
     except Exception as e:
@@ -131,10 +118,10 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
         title=f"📊 Sales Analytics Dashboard - Last {period.title()}",
         title_x=0.5,
         showlegend=False,
-        height=900,
-        font=dict(size=11),
+        height=1100,
+        font=dict(size=12),
         template="plotly_white",
-        margin=dict(t=100, b=60, l=60, r=60)
+        margin=dict(t=120, b=80, l=80, r=80)
     )
     
     # Update axes labels
@@ -142,11 +129,8 @@ def create_sales_dashboard(sales_data: pd.DataFrame, period: str = "week") -> go
     fig.update_yaxes(title_text="Revenue (₽)", row=1, col=1)
     fig.update_yaxes(title_text="Quantity", secondary_y=True, row=1, col=1)
     
-    fig.update_xaxes(title_text="Revenue (₽)", row=1, col=2)
-    fig.update_yaxes(title_text="Products", row=1, col=2)
-    
-    fig.update_xaxes(title_text="Order Value (₽)", row=2, col=2)
-    fig.update_yaxes(title_text="Frequency", row=2, col=2)
+    fig.update_xaxes(title_text="Revenue (₽)", row=2, col=1)
+    fig.update_yaxes(title_text="Products", row=2, col=1)
     
     return fig
 
@@ -165,17 +149,17 @@ def create_inventory_dashboard(forecast_data: pd.DataFrame) -> go.Figure:
     
     # Create subplot layout
     fig = make_subplots(
-        rows=2, cols=2,
+        rows=3, cols=1,
         subplot_titles=[
             "🚨 Risk Level Distribution",
             "⏰ Days Until Stockout",
-            "📦 Current Stock Levels", 
-            "🎯 Reorder Point Analysis"
+            "📦 Current Stock Levels"
         ],
-        specs=[[{"type": "pie"}, {"type": "bar"}],
-               [{"type": "bar"}, {"type": "scatter"}]],
-        vertical_spacing=0.20,
-        horizontal_spacing=0.15
+        specs=[[{"type": "pie"}],
+               [{"type": "bar"}],
+               [{"type": "bar"}]],
+        vertical_spacing=0.15,
+        row_heights=[0.35, 0.35, 0.30]
     )
     
     try:
@@ -224,13 +208,13 @@ def create_inventory_dashboard(forecast_data: pd.DataFrame) -> go.Figure:
                     marker_color=bar_colors,
                     hovertemplate='<b>%{y}</b><br>Days: %{x:.1f}<extra></extra>'
                 ),
-                row=1, col=2
+                row=2, col=1
             )
         
-        # 3. Current Stock Levels (Bottom Left)
+        # 3. Current Stock Levels (Third Row)
         if 'current_stock' in forecast_data.columns and 'product_name' in forecast_data.columns:
-            # Take top 15 products by stock level
-            stock_data = forecast_data.nlargest(15, 'current_stock')
+            # Take top 10 products by stock level for better visibility
+            stock_data = forecast_data.nlargest(10, 'current_stock')
             
             fig.add_trace(
                 go.Bar(
@@ -240,50 +224,9 @@ def create_inventory_dashboard(forecast_data: pd.DataFrame) -> go.Figure:
                     marker_color='#2E86AB',
                     hovertemplate='<b>%{x}</b><br>Stock: %{y}<extra></extra>'
                 ),
-                row=2, col=1
-            )
-        
-        # 4. Reorder Point Analysis (Bottom Right)
-        if all(col in forecast_data.columns for col in ['current_stock', 'recommended_reorder_point', 'product_name']):
-            # Take subset for readability
-            reorder_data = forecast_data.head(20)
-            
-            # Current stock scatter
-            fig.add_trace(
-                go.Scatter(
-                    x=reorder_data.index,
-                    y=reorder_data['current_stock'],
-                    mode='markers',
-                    name='Current Stock',
-                    marker=dict(
-                        size=10,
-                        color='#2E86AB',
-                        symbol='circle'
-                    ),
-                    hovertemplate='<b>%{text}</b><br>Current Stock: %{y}<extra></extra>',
-                    text=reorder_data['product_name']
-                ),
-                row=2, col=2
-            )
-            
-            # Reorder point line
-            fig.add_trace(
-                go.Scatter(
-                    x=reorder_data.index,
-                    y=reorder_data['recommended_reorder_point'],
-                    mode='markers+lines',
-                    name='Reorder Point',
-                    marker=dict(
-                        size=8,
-                        color='#A23B72',
-                        symbol='diamond'
-                    ),
-                    line=dict(color='#A23B72', dash='dash'),
-                    hovertemplate='<b>%{text}</b><br>Reorder Point: %{y}<extra></extra>',
-                    text=reorder_data['product_name']
-                ),
-                row=2, col=2
+                row=3, col=1
             )
+
     
     except Exception as e:
         logger.error(f"Error creating inventory dashboard: {str(e)}")
@@ -293,22 +236,19 @@ def create_inventory_dashboard(forecast_data: pd.DataFrame) -> go.Figure:
     fig.update_layout(
         title="📦 Inventory Risk Analysis Dashboard",
         title_x=0.5,
-        showlegend=True,
-        height=900,
-        font=dict(size=11),
+        showlegend=False,
+        height=1100,
+        font=dict(size=12),
         template="plotly_white",
-        margin=dict(t=100, b=60, l=60, r=60)
+        margin=dict(t=120, b=80, l=80, r=80)
     )
     
     # Update axes
-    fig.update_xaxes(title_text="Days", row=1, col=2)
-    fig.update_yaxes(title_text="Products", row=1, col=2)
-    
-    fig.update_xaxes(title_text="Products", row=2, col=1, tickangle=45)
-    fig.update_yaxes(title_text="Stock Quantity", row=2, col=1)
+    fig.update_xaxes(title_text="Days", row=2, col=1)
+    fig.update_yaxes(title_text="Products", row=2, col=1)
     
-    fig.update_xaxes(title_text="Product Index", row=2, col=2)
-    fig.update_yaxes(title_text="Quantity", row=2, col=2)
+    fig.update_xaxes(title_text="Products", row=3, col=1, tickangle=45)
+    fig.update_yaxes(title_text="Stock Quantity", row=3, col=1)
     
     return fig