Update app.py

app.py

@@ -7,6 +7,7 @@ import plotly.graph_objs as go
 from plotly.subplots import make_subplots
 import plotly.express as px
 import datetime
+import numpy as np
 
 # Function to fetch renewable energy data
 def get_renewable_energy_data(city_code):
@@ -262,4 +263,15 @@ if st.button('Calculate Optimal Energy Mix'):
 
                 if correlation_matrix is not None:
                     fig_corr = px.imshow(correlation_matrix, title='Correlation Matrix of Renewable Capacity Factors', labels={'color': 'Correlation'}, template='plotly_white')
-                    st.plotly_chart(fig_corr, use_container_width=True, height=800)
+                    st.plotly_chart(fig_corr, use_container_width=True, height=800)
+
+        # Plot heatmaps for renewable energy and demand characteristics
+        st.markdown("### Heatmap of Renewable Energy and Demand Characteristics")
+        hourly_data = numeric_energy_data_df.copy()
+        hourly_data['Date'] = pd.to_datetime(data['Time']).dt.date
+        hourly_data['Hour'] = pd.to_datetime(data['Time']).dt.hour
+        
+        for column in hourly_data.columns[2:]:  # Skipping 'Date' and 'Hour' columns
+            pivot_df = hourly_data.pivot_table(index='Hour', columns='Date', values=column, aggfunc=np.mean)
+            fig_heatmap = px.imshow(pivot_df, title=f"Heatmap of {column}", labels={'color': column}, template='plotly_white', aspect='auto')
+            st.plotly_chart(fig_heatmap, use_container_width=True, height=800)