Update app.py

app.py

@@ -172,33 +172,6 @@ def create_shift_trend_chart(df, time_period='daily'):
         fig.update_layout(height=400)
     
     return fig
-    """Create individual materials trend chart"""
-    if selected_materials:
-        df = df[df['material_type'].isin(selected_materials)]
-    
-    if time_period == 'daily':
-        grouped = df.groupby(['date', 'material_type'])['weight_kg'].sum().reset_index()
-        fig = px.line(grouped, x='date', y='weight_kg', color='material_type',
-                     title='🏷️ Materials Production Trends',
-                     labels={'weight_kg': 'Weight (kg)', 'date': 'Date', 'material_type': 'Material'})
-    elif time_period == 'weekly':
-        df['week'] = df['date'].dt.isocalendar().week
-        df['year'] = df['date'].dt.year
-        grouped = df.groupby(['year', 'week', 'material_type'])['weight_kg'].sum().reset_index()
-        grouped['week_label'] = grouped['year'].astype(str) + '-W' + grouped['week'].astype(str)
-        fig = px.bar(grouped, x='week_label', y='weight_kg', color='material_type',
-                    title='🏷️ Materials Production Trends (Weekly)',
-                    labels={'weight_kg': 'Weight (kg)', 'week_label': 'Week', 'material_type': 'Material'})
-    else:  # monthly
-        df['month'] = df['date'].dt.to_period('M')
-        grouped = df.groupby(['month', 'material_type'])['weight_kg'].sum().reset_index()
-        grouped['month'] = grouped['month'].astype(str)
-        fig = px.bar(grouped, x='month', y='weight_kg', color='material_type',
-                    title='🏷️ Materials Production Trends (Monthly)',
-                    labels={'weight_kg': 'Weight (kg)', 'month': 'Month', 'material_type': 'Material'})
-    
-    fig.update_layout(height=400)
-    return fig
 
 def detect_outliers(df):
     outliers = {}
@@ -285,25 +258,18 @@ def main():
         
         col_total1, col_total2 = st.columns([3, 1])
         
+        with col_total2:
+            total_time_view = st.selectbox("Total Time Period", ["daily", "weekly", "monthly"], key="total_time")
+        
         with col_total1:
             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([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")
             
@@ -315,6 +281,13 @@ def main():
                 help="Choose which materials to display"
             )
         
+        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")
+        
         # Shift Analysis
         if 'shift' in df.columns:
             st.subheader("🌓 Shift Analysis")
@@ -322,14 +295,14 @@ def main():
             # Shift time trend controls moved to right
             col_shift_trend1, col_shift_trend2 = st.columns([3, 1])
             
+            with col_shift_trend2:
+                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)
             
-            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**")
             shift_col1, shift_col2 = st.columns(2)