Update modules/visuals.py

modules/visuals.py

@@ -4,14 +4,15 @@ import pandas as pd
 
 def display_dashboard(df):
     st.subheader("📊 System Summary")
-    col1, col2, col3 = st.columns(3)
+    col1, col2, col3, col4 = st.columns(4)
     col1.metric("Total Poles", df.shape[0])
     col2.metric("🚨 Red Alerts", df[df['AlertLevel'] == "Red"].shape[0])
     col3.metric("⚡ Power Issues", df[df['PowerSufficient'] == "No"].shape[0])
+    col4.metric("📍 Locations", len(df['Location'].unique()))
 
 def display_charts(df):
     st.subheader("⚙️ Energy Generation Trends")
-    st.bar_chart(df.set_index("PoleID")[["SolarGen(kWh)", "WindGen(kWh)"]])
+    st.bar_chart(df.groupby("Location")[["SolarGen(kWh)", "WindGen(kWh)"]].sum())
     st.subheader("📉 Tilt vs Vibration")
     st.scatter_chart(df.rename(columns={"Tilt(°)": "Tilt", "Vibration(g)": "Vibration"}).set_index("PoleID")[["Tilt", "Vibration"]])
 
@@ -20,8 +21,18 @@ def display_heatmap(df):
     alert_map = {"Green": 0, "Yellow": 1, "Red": 2}
     df["AlertValue"] = df["AlertLevel"].map(alert_map)
     
-    # Create a pivot table for heatmap (single row for all poles)
-    pivot_df = df[["PoleID", "AlertValue"]].set_index("PoleID").T
+    # Pivot table: Locations as rows, Poles as columns
+    pivot_df = df.pivot_table(index="Location", columns="PoleID", values="AlertValue", fill_value=0)
+    
+    # Create hover text with PoleID, AlertLevel, and Anomalies
+    hover_df = df.pivot_table(index="Location", columns="PoleID", values=["PoleID", "AlertLevel", "Anomalies"], aggfunc="first")
+    hover_text = pivot_df.copy()
+    for loc in pivot_df.index:
+        for pole in pivot_df.columns:
+            if pole in hover_df.loc[loc, "PoleID"].columns:
+                alert = hover_df.loc[loc, ("AlertLevel", pole)] if pd.notna(hover_df.loc[loc, ("AlertLevel", pole)]) else "None"
+                anomalies = hover_df.loc[loc, ("Anomalies", pole)] if pd.notna(hover_df.loc[loc, ("Anomalies", pole)]) else "None"
+                hover_text.loc[loc, pole] = f"Pole: {pole}<br>Alert: {alert}<br>Anomalies: {anomalies}"
     
     # Create heatmap using Plotly
     fig = px.imshow(
@@ -29,14 +40,14 @@ def display_heatmap(df):
         color_continuous_scale=["green", "yellow", "red"],
         zmin=0,
         zmax=2,
-        labels=dict(color="Alert Level"),
-        title="Pole Alert Heatmap",
-        height=300
+        title="Pole Alert Heatmap by Location",
+        text_auto=False,
+        height=500
     )
+    fig.update_traces(hovertemplate="%{customdata}<br>%{x}<br>%{y}", customdata=hover_text)
     fig.update_layout(
         xaxis_title="Pole ID",
-        yaxis_title="",
-        yaxis_showticklabels=False,
+        yaxis_title="Location",
         coloraxis_colorbar=dict(
             tickvals=[0, 1, 2],
             ticktext=["Green", "Yellow", "Red"]