Update app.py

app.py

@@ -4,6 +4,8 @@ import numpy as np
 import plotly.express as px
 from transformers import pipeline
 from datasets import load_dataset
+import folium
+from streamlit_folium import st_folium
 
 # Hugging Face Datasets
 @st.cache_data
@@ -36,6 +38,8 @@ def generate_terrain_data():
     np.random.seed(42)
     data = {
         "Region": [f"Region-{i}" for i in range(1, 11)],
+        "Latitude": np.random.uniform(30.0, 50.0, size=10),
+        "Longitude": np.random.uniform(-120.0, -70.0, size=10),
         "Terrain Difficulty (0-10)": np.random.randint(1, 10, size=10),
         "Signal Strength (dBm)": np.random.randint(-120, -30, size=10),
         "Cost ($1000s)": np.random.randint(50, 200, size=10),
@@ -67,6 +71,27 @@ elif data_to_view == "Filtered Terrain Data":
     st.subheader("Filtered Terrain Data")
     st.dataframe(filtered_data)
 
+# Map Visualization
+st.header("Geographical Map of Regions")
+if not filtered_data.empty:
+    map_center = [filtered_data["Latitude"].mean(), filtered_data["Longitude"].mean()]
+    region_map = folium.Map(location=map_center, zoom_start=6)
+
+    for _, row in filtered_data.iterrows():
+        folium.Marker(
+            location=[row["Latitude"], row["Longitude"]],
+            popup=(
+                f"<b>Region:</b> {row['Region']}<br>"
+                f"<b>Signal Strength:</b> {row['Signal Strength (dBm)']} dBm<br>"
+                f"<b>Cost:</b> ${row['Cost ($1000s)']}k<br>"
+                f"<b>Terrain Difficulty:</b> {row['Terrain Difficulty (0-10)']}"
+            ),
+        ).add_to(region_map)
+
+    st_folium(region_map, width=700, height=500)
+else:
+    st.write("No regions match the selected criteria.")
+
 # Visualization
 fig = px.scatter(
     filtered_data,