Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import pydeck as pdk
import plotly.express as px
from datetime import datetime, time
import json

st.set_page_config(layout="wide", page_title="Shibuya Education Map")

# Generate mock data
@st.cache_data
def generate_mock_data():
    # Shibuya coordinates
    SHIBUYA_LAT = 35.6580
    SHIBUYA_LON = 139.7016
    
    # Nursery schools
    np.random.seed(42)
    n_nurseries = 25
    nurseries = pd.DataFrame({
        'name': [f'Nursery School {i+1}' for i in range(n_nurseries)],
        'lat': SHIBUYA_LAT + np.random.normal(0, 0.01, n_nurseries),
        'lon': SHIBUYA_LON + np.random.normal(0, 0.01, n_nurseries),
        'children': np.random.randint(20, 100, n_nurseries),
        'type': np.random.choice(['Public', 'Private'], n_nurseries),
        'opening_time': [time(7, 0) for _ in range(n_nurseries)],
        'closing_time': [time(18, 0) for _ in range(n_nurseries)],
        'borough': np.random.choice(['Shibuya', 'Harajuku', 'Ebisu', 'Daikanyama'], n_nurseries)
    })
    
    # Elementary schools
    n_elementary = 20
    elementary = pd.DataFrame({
        'name': [f'Elementary School {i+1}' for i in range(n_elementary)],
        'lat': SHIBUYA_LAT + np.random.normal(0, 0.015, n_elementary),
        'lon': SHIBUYA_LON + np.random.normal(0, 0.015, n_elementary),
        'students': np.random.randint(200, 800, n_elementary),
        'borough': np.random.choice(['Shibuya', 'Harajuku', 'Ebisu', 'Daikanyama'], n_elementary)
    })
    
    # Bus stops
    n_stops = 100
    bus_stops = pd.DataFrame({
        'name': [f'Bus Stop {i+1}' for i in range(n_stops)],
        'lat': SHIBUYA_LAT + np.random.normal(0, 0.02, n_stops),
        'lon': SHIBUYA_LON + np.random.normal(0, 0.02, n_stops),
        'borough': np.random.choice(['Shibuya', 'Harajuku', 'Ebisu', 'Daikanyama'], n_stops)
    })
    
    # Generate bus routes
    n_routes = 5
    routes = []
    for i in range(n_routes):
        n_points = np.random.randint(10, 20)
        route = pd.DataFrame({
            'path_lat': SHIBUYA_LAT + np.random.normal(0, 0.02, n_points),
            'path_lon': SHIBUYA_LON + np.random.normal(0, 0.02, n_points),
            'route_id': i
        })
        routes.append(route)
    bus_routes = pd.concat(routes)
    
    return nurseries, elementary, bus_stops, bus_routes

nurseries, elementary, bus_stops, bus_routes = generate_mock_data()

# Sidebar controls
st.sidebar.title("Map Controls")

# Borough filter
boroughs = ['All'] + sorted(nurseries['borough'].unique().tolist())
selected_borough = st.sidebar.selectbox('Select Borough', boroughs)

# Layer toggles
show_nurseries = st.sidebar.checkbox('Show Nursery Schools', True)
show_elementary = st.sidebar.checkbox('Show Elementary Schools', True)
show_bus_stops = st.sidebar.checkbox('Show Bus Stops', True)
show_bus_routes = st.sidebar.checkbox('Show Bus Routes', True)

# Time slider
time_range = st.sidebar.slider(
    "Time of Day",
    min_value=time(6, 0),
    max_value=time(20, 0),
    value=time(12, 0),
    format="HH:mm"
)

# Map style
map_style = st.sidebar.selectbox(
    'Map Style',
    ['mapbox://styles/mapbox/light-v9', 'mapbox://styles/mapbox/satellite-v9']
)

# Color scheme
color_scheme = st.sidebar.selectbox(
    'Color Scheme',
    ['default', 'viridis', 'plasma']
)

# Filter data based on borough selection
if selected_borough != 'All':
    nurseries = nurseries[nurseries['borough'] == selected_borough]
    elementary = elementary[elementary['borough'] == selected_borough]
    bus_stops = bus_stops[bus_stops['borough'] == selected_borough]

# Create layers
layers = []

if show_nurseries:
    nursery_layer = pdk.Layer(
        'ScatterplotLayer',
        nurseries,
        get_position=['lon', 'lat'],
        get_radius=100,
        get_fill_color=[255, 0, 0, 140],
        pickable=True
    )
    layers.append(nursery_layer)

if show_elementary:
    elementary_layer = pdk.Layer(
        'ScatterplotLayer',
        elementary,
        get_position=['lon', 'lat'],
        get_radius=150,
        get_fill_color=[0, 0, 255, 140],
        pickable=True
    )
    layers.append(elementary_layer)

if show_bus_stops:
    bus_stop_layer = pdk.Layer(
        'ScatterplotLayer',
        bus_stops,
        get_position=['lon', 'lat'],
        get_radius=50,
        get_fill_color=[0, 255, 0, 140],
        pickable=True
    )
    layers.append(bus_stop_layer)

if show_bus_routes:
    bus_route_layer = pdk.Layer(
        'PathLayer',
        bus_routes,
        get_path=['path_lon', 'path_lat'],
        get_width=20,
        get_color=[255, 255, 0, 80],
        pickable=True
    )
    layers.append(bus_route_layer)

# Create the map
st.title("Shibuya Education Map")

col1, col2 = st.columns([3, 1])

with col1:
    view_state = pdk.ViewState(
        latitude=35.6580,
        longitude=139.7016,
        zoom=13,
        pitch=45
    )

    deck = pdk.Deck(
        map_style=map_style,
        initial_view_state=view_state,
        layers=layers,
        tooltip={
            "html": "<b>Name:</b> {name}<br/>"
                   "<b>Borough:</b> {borough}<br/>"
                   "<b>Type:</b> {type}<br/>"
                   "<b>Children:</b> {children}"
        }
    )

    st.pydeck_chart(deck)

# Stats panel
with col2:
    st.subheader("Statistics")
    
    # Nursery schools stats
    st.write("**Nursery Schools**")
    st.write(f"Total: {len(nurseries)}")
    st.write(f"Total children: {nurseries['children'].sum()}")
    
    # Plot nursery types distribution
    fig = px.pie(nurseries, names='type', title='Nursery Types')
    st.plotly_chart(fig, use_container_width=True)
    
    # Elementary schools stats
    st.write("**Elementary Schools**")
    st.write(f"Total: {len(elementary)}")
    st.write(f"Total students: {elementary['students'].sum()}")
    
    # Bus infrastructure
    st.write("**Bus Infrastructure**")
    st.write(f"Bus stops: {len(bus_stops)}")
    st.write(f"Bus routes: {len(bus_routes['route_id'].unique())}")

    # Borough distribution
    if selected_borough == 'All':
        st.write("**Facilities by Borough**")
        borough_counts = pd.concat([
            nurseries['borough'].value_counts(),
            elementary['borough'].value_counts(),
            bus_stops['borough'].value_counts()
        ]).reset_index()
        borough_counts.columns = ['Borough', 'Count']
        fig = px.bar(borough_counts, x='Borough', y='Count', title='Facilities by Borough')
        st.plotly_chart(fig, use_container_width=True)