Create modules/visuals.py

modules/visuals.py

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+
+
+import streamlit as st
+import plotly.express as px
+import pandas as pd
+
+def display_dashboard(df: pd.DataFrame):
+    st.subheader("📊 System Summary")
+    col1, col2, col3, col4 = st.columns(4)
+
+    col1.metric("Total Poles", df.shape[0])
+    col2.metric("🚨 Red Alerts", df[df["Alert_Level__c"] == "Red"].shape[0])
+    col3.metric("⚡ Power Issues", df[df["Power_Sufficient__c"] == "No"].shape[0])
+    col4.metric("📷 Offline Cameras", df[df["Camera_Status__c"] == "Offline"].shape[0])
+
+def display_charts(df: pd.DataFrame):
+    st.subheader("⚙ Energy Generation")
+    fig_energy = px.bar(
+        df,
+        x="Name",
+        y=["Solar_Generation__c", "Wind_Generation__c"],
+        barmode="group",
+        title="Solar vs Wind Generation"
+    )
+    st.plotly_chart(fig_energy)
+
+    st.subheader("🎥 Camera Status Distribution")
+    fig_camera = px.pie(
+        df,
+        names="Camera_Status__c",
+        title="Camera Status",
+        hole=0.4
+    )
+    st.plotly_chart(fig_camera)
+
+    st.subheader("🚨 Alert Level Breakdown")
+    fig_alerts = px.histogram(
+        df,
+        x="Alert_Level__c",
+        title="Number of Poles by Alert Level"
+    )
+    st.plotly_chart(fig_alerts)