Create modules/visuals.py

modules/visuals.py

@@ -0,0 +1,35 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+
+def display_summary(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["AlertLevel"] == "Red"].shape[0])
+    col3.metric("Power Issues", df[df["PowerSufficient"] == "No"].shape[0])
+    col4.metric("Offline Cameras", df[df["CameraStatus"] == "Offline"].shape[0])
+
+def display_tel_map(df: pd.DataFrame):
+    st.subheader("🗺️ Telangana Pole Heatmap")
+    red_df = df[df["AlertLevel"] == "Red"]
+    fig = px.scatter_mapbox(
+        red_df,
+        lat="Location_Latitude",
+        lon="Location_Longitude",
+        color="AlertLevel",
+        hover_name="PoleID",
+        zoom=6.3,
+        height=500,
+        mapbox_style="carto-positron"
+    )
+    st.plotly_chart(fig, use_container_width=True)
+
+def display_energy_trends(df: pd.DataFrame):
+    st.subheader("⚙️ Solar vs Wind")
+    st.plotly_chart(px.bar(df, x="PoleID", y=["SolarGen(kWh)", "WindGen(kWh)"], barmode="group"))
+
+def display_scatter(df: pd.DataFrame):
+    st.subheader("📉 Tilt vs Vibration")
+    fig = px.scatter(df, x="Tilt(°)", y="Vibration(g)", color="AlertLevel", hover_data=["PoleID", "Site"])
+    st.plotly_chart(fig)