Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+from geopy.distance import geodesic
+
+# Create a DataFrame with sample data
+data = pd.DataFrame({
+    'lat': np.random.uniform(-90, 90, 1000),
+    'lon': np.random.uniform(-180, 180, 1000),
+    'value': np.random.rand(1000) * 100
+})
+
+# Function to calculate distance in meters between two coordinates
+def calculate_distance(lat1, lon1, lat2, lon2):
+    coords_1 = (lat1, lon1)
+    coords_2 = (lat2, lon2)
+    return geodesic(coords_1, coords_2).meters
+
+# Display a title
+st.title('Geospatial Dashboard')
+
+# Dropdown to select specific coordinates
+selected_coords = st.selectbox('Select Coordinates', ['Random', 'Custom'])
+if selected_coords == 'Custom':
+    custom_lat = st.number_input('Enter Latitude', value=0.0)
+    custom_lon = st.number_input('Enter Longitude', value=0.0)
+else:
+    custom_lat, custom_lon = 0.0, 0.0
+
+# Slider for setting the zoom level
+zoom_level = st.slider('Zoom Level', min_value=1, max_value=15, value=5)
+
+# Slider to set the radius in meters
+radius_in_meters = st.slider('Select Radius (in meters)', min_value=100, max_value=5000, value=1000)
+
+# Filter data based on the radius
+if selected_coords == 'Custom':
+    filtered_data = data[data.apply(lambda x: calculate_distance(x['lat'], x['lon'], custom_lat, custom_lon), axis=1) <= radius_in_meters]
+    st.map(filtered_data, zoom=zoom_level, use_container_width=True)
+else:
+    st.map(data, zoom=zoom_level, use_container_width=True)