Update app.py

app.py

@@ -110,13 +110,48 @@ def create_materials_trend_chart(df, time_period='daily', selected_materials=Non
     return fig
 
 def create_shift_trend_chart(df, time_period='daily'):
-    """Create shift production trend chart over time"""
+    """Create shift production trend chart over time with stacked bars"""
     if time_period == 'daily':
+        # Create stacked bar chart where each bar is one day
         grouped = df.groupby(['date', 'shift'])['weight_kg'].sum().reset_index()
-        fig = px.bar(grouped, x='date', y='weight_kg', color='shift',
-                     title='📅 Daily Shift Production Trends',
-                     labels={'weight_kg': 'Weight (kg)', 'date': 'Date', 'shift': 'Shift'},
-                     barmode='group')
+        
+        # Pivot to have shifts as columns
+        pivot_data = grouped.pivot(index='date', columns='shift', values='weight_kg').fillna(0)
+        
+        fig = go.Figure()
+        
+        # Add day shift (bottom of stack)
+        if 'day' in pivot_data.columns:
+            fig.add_trace(go.Bar(
+                x=pivot_data.index,
+                y=pivot_data['day'],
+                name='Day Shift',
+                marker_color='#FFA500',
+                text=pivot_data['day'].round(0),
+                textposition='inside'
+            ))
+        
+        # Add night shift (top of stack)  
+        if 'night' in pivot_data.columns:
+            fig.add_trace(go.Bar(
+                x=pivot_data.index,
+                y=pivot_data['night'],
+                name='Night Shift',
+                marker_color='#4169E1',
+                base=pivot_data['day'] if 'day' in pivot_data.columns else 0,
+                text=pivot_data['night'].round(0),
+                textposition='inside'
+            ))
+            
+        fig.update_layout(
+            title='📅 Daily Shift Production Trends (Stacked)',
+            xaxis_title='Date',
+            yaxis_title='Weight (kg)',
+            barmode='stack',
+            height=400,
+            showlegend=True
+        )
+        
     elif time_period == 'weekly':
         df['week'] = df['date'].dt.isocalendar().week
         df['year'] = df['date'].dt.year
@@ -125,7 +160,7 @@ def create_shift_trend_chart(df, time_period='daily'):
         fig = px.bar(grouped, x='week_label', y='weight_kg', color='shift',
                     title='📅 Weekly Shift Production Trends',
                     labels={'weight_kg': 'Weight (kg)', 'week_label': 'Week', 'shift': 'Shift'},
-                    barmode='group')
+                    barmode='stack')
     else:  # monthly
         df['month'] = df['date'].dt.to_period('M')
         grouped = df.groupby(['month', 'shift'])['weight_kg'].sum().reset_index()
@@ -133,9 +168,9 @@ def create_shift_trend_chart(df, time_period='daily'):
         fig = px.bar(grouped, x='month', y='weight_kg', color='shift',
                     title='📅 Monthly Shift Production Trends',
                     labels={'weight_kg': 'Weight (kg)', 'month': 'Month', 'shift': 'Shift'},
-                    barmode='group')
+                    barmode='stack')
+        fig.update_layout(height=400)
     
-    fig.update_layout(height=400)
     return fig
     """Create individual materials trend chart"""
     if selected_materials:
@@ -248,21 +283,28 @@ def main():
         # Total Production Chart Section
         st.subheader("📊 Total Production Trends")
         
-        col_total1, col_total2 = st.columns([1, 3])
+        col_total1, col_total2 = st.columns([3, 1])
         
         with col_total1:
-            total_time_view = st.selectbox("Total Time Period", ["daily", "weekly", "monthly"], key="total_time")
-        
-        with col_total2:
             total_chart = create_total_production_chart(df, total_time_view)
             st.plotly_chart(total_chart, use_container_width=True)
         
+        with col_total2:
+            total_time_view = st.selectbox("Total Time Period", ["daily", "weekly", "monthly"], key="total_time")
+        
         # Materials Production Chart Section
         st.subheader("🏷️ Materials Production Trends")
         
-        col_mat1, col_mat2 = st.columns([1, 3])
+        col_mat1, col_mat2 = st.columns([3, 1])
         
         with col_mat1:
+            if selected_materials:
+                materials_chart = create_materials_trend_chart(df, materials_time_view, selected_materials)
+                st.plotly_chart(materials_chart, use_container_width=True)
+            else:
+                st.info("Please select materials to display trends")
+        
+        with col_mat2:
             materials_time_view = st.selectbox("Materials Time Period", ["daily", "weekly", "monthly"], key="materials_time")
             
             selected_materials = st.multiselect(
@@ -273,27 +315,20 @@ def main():
                 help="Choose which materials to display"
             )
         
-        with col_mat2:
-            if selected_materials:
-                materials_chart = create_materials_trend_chart(df, materials_time_view, selected_materials)
-                st.plotly_chart(materials_chart, use_container_width=True)
-            else:
-                st.info("Please select materials to display trends")
-        
         # Shift Analysis
         if 'shift' in df.columns:
             st.subheader("🌓 Shift Analysis")
             
-            # Shift time trend controls
-            col_shift_ctrl, col_shift_space = st.columns([2, 2])
+            # Shift time trend controls moved to right
+            col_shift_trend1, col_shift_trend2 = st.columns([3, 1])
             
-            with col_shift_ctrl:
-                shift_time_view = st.selectbox("Shift Time Period", ["daily", "weekly", "monthly"], key="shift_time")
+            with col_shift_trend1:
+                st.markdown("**📈 Shift Production Trends**")
+                shift_trend_chart = create_shift_trend_chart(df, shift_time_view)
+                st.plotly_chart(shift_trend_chart, use_container_width=True)
             
-            # Daily shift trend chart
-            st.markdown("**📈 Shift Production Trends**")
-            shift_trend_chart = create_shift_trend_chart(df, shift_time_view)
-            st.plotly_chart(shift_trend_chart, use_container_width=True)
+            with col_shift_trend2:
+                shift_time_view = st.selectbox("Shift Time Period", ["daily", "weekly", "monthly"], key="shift_time")
             
             # Shift comparison charts
             st.markdown("**📊 Shift Comparison Analysis**")