Update app.py

app.py

@@ -1,5 +1,3 @@
-
-You said:
 import random
 import pandas as pd
 import streamlit as st
@@ -130,138 +128,6 @@ st.pydeck_chart(pdk.Deck(
     }
 ))
 
-# ---- Data Table ----
-st.subheader("📋 Detailed Pole Information")
-st.dataframe(filtered_df, use_container_width=True)                                                                                              import random
-import pandas as pd
-import streamlit as st
-import pydeck as pdk
-
-# ---- Area-Specific Configuration ----
-AREA_DETAILS = {
-    "Hyderabad": {
-        "coords": [17.4036, 78.5247],
-        "area_name": "Ramanthapur Dairy Farm",
-        "purpose": "Dairy Farm"
-    },
-    "Ballari": {
-        "coords": [15.1468, 76.9237],
-        "area_name": "Cowl Bazar Power Station",
-        "purpose": "Power Station"
-    },
-    "Gadwal": {
-        "coords": [16.2315, 77.7965],
-        "area_name": "Bheem Nagar Solar Station",
-        "purpose": "Solar Station"
-    },
-    "Kurnool": {
-        "coords": [15.8281, 78.0373],
-        "area_name": "Venkata Ramana Agriculture Field",
-        "purpose": "Agriculture Monitoring"
-    }
-}
-
-POLES_PER_SITE = 12
-
-# ---- Generate Poles with Anomalies ----
-def generate_open_area_poles(site_name, center_lat, center_lon, area, purpose):
-    poles = []
-    spacing = 0.0006
-    anomalies_options = ['None', 'Sensor Fault', 'Overheat', 'Power Surge']
-    anomaly_weights = [0.6, 0.2, 0.1, 0.1]
-
-    for i in range(POLES_PER_SITE):
-        lat = center_lat + random.uniform(-0.0002, 0.0002)
-        lon = center_lon + (i - POLES_PER_SITE // 2) * spacing
-        alert_level = random.choices(['Green', 'Yellow', 'Red'], weights=[6, 4, 2])[0]
-        anomaly = random.choices(anomalies_options, weights=anomaly_weights)[0]
-
-        poles.append({
-            "Pole ID": f"{site_name[:3].upper()}-{i+1:03}",
-            "Site": site_name,
-            "Latitude": lat,
-            "Longitude": lon,
-            "Alert Level": alert_level,
-            "Health Score": round(random.uniform(70, 100), 2),
-            "Power Status": random.choice(['Sufficient', 'Insufficient']),
-            "Camera Status": random.choice(['Online', 'Offline']),
-            "Location Area": area,
-            "Purpose": purpose,
-            "Anomalies": anomaly
-        })
-    return poles
-
-# ---- Prepare Full DataFrame ----
-all_poles = []
-for site, details in AREA_DETAILS.items():
-    poles = generate_open_area_poles(site, *details['coords'], details['area_name'], details['purpose'])
-    all_poles.extend(poles)
-
-df = pd.DataFrame(all_poles)
-
-# ---- Streamlit UI ----
-st.set_page_config(page_title="Smart Pole Visual Dashboard", layout="wide")
-st.title("🌐 Smart Renewable Pole Monitoring Dashboard")
-
-site = st.selectbox("📍 Select a site location:", list(AREA_DETAILS.keys()))
-selected = AREA_DETAILS[site]
-
-# ---- Filtered View ----
-filtered_df = df[df["Site"] == site]
-
-# ---- Display Site Description ----
-st.markdown(f"### 📌 Location: **{selected['area_name']}**")
-st.markdown(f"🔧 **Poles Purpose**: {selected['purpose']}")
-
-# ---- KPI Metrics ----
-col1, col2, col3 = st.columns(3)
-col1.metric("Total Poles", POLES_PER_SITE)
-col2.metric("🔴 Red Alerts", filtered_df[filtered_df["Alert Level"] == "Red"].shape[0])
-col3.metric("📷 Offline Cameras", filtered_df[filtered_df["Camera Status"] == "Offline"].shape[0])
-
-# ---- Alert Level to Color ----
-def alert_color(alert):
-    return {
-        "Green": [0, 255, 0, 160],
-        "Yellow": [255, 255, 0, 160],
-        "Red": [255, 0, 0, 160]
-    }[alert]
-
-filtered_df = filtered_df.copy()
-filtered_df["Color"] = filtered_df["Alert Level"].apply(alert_color)
-
-# ---- Map Visualization ----
-st.subheader("🗺️ Pole Location & Health Status")
-st.pydeck_chart(pdk.Deck(
-    initial_view_state=pdk.ViewState(
-        latitude=selected['coords'][0],
-        longitude=selected['coords'][1],
-        zoom=16.5,
-        pitch=45
-    ),
-    layers=[
-        pdk.Layer(
-            "ScatterplotLayer",
-            data=filtered_df,
-            get_position='[Longitude, Latitude]',
-            get_color='Color',
-            get_radius=30,
-            pickable=True
-        )
-    ],
-    tooltip={
-        "html": "<b>Pole ID:</b> {Pole ID}<br/>"
-                "<b>Location:</b> {Location Area}<br/>"
-                "<b>Purpose:</b> {Purpose}<br/>"
-                "<b>Health Score:</b> {Health Score}<br/>"
-                "<b>Alert Level:</b> {Alert Level}<br/>"
-                "<b>Camera:</b> {Camera Status}<br/>"
-                "<b>Power:</b> {Power Status}<br/>"
-                "<b>Anomaly:</b> {Anomalies}",
-        "style": {"color": "white", "backgroundColor": "black"}
-    }
-))
-
 # ---- Data Table ----
 st.subheader("📋 Detailed Pole Information")
 st.dataframe(filtered_df, use_container_width=True)