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, timedelta

# Page config
st.set_page_config(layout="wide", page_title="NYC Interactive Map")

# Initialize session state
if "layer_states" not in st.session_state:
    st.session_state.layer_states = {
        "food_trucks": True,
        "pedestrians": True,
        "routes": False,
        "taxis": False
    }

# Title and description
st.title("NYC Interactive Map")
st.markdown("Explore New York City's dynamic urban landscape with this interactive visualization.")

# Sidebar controls
st.sidebar.header("Controls")

# Time control
current_time = st.sidebar.slider(
    "Time of Day",
    min_value=datetime.strptime("00:00", "%H:%M"),
    max_value=datetime.strptime("23:59", "%H:%M"),
    value=datetime.strptime("12:00", "%H:%M"),
    format="HH:mm"
)

# Borough filter
boroughs = ['All', 'Manhattan', 'Brooklyn', 'Queens', 'Bronx', 'Staten Island']
selected_borough = st.sidebar.selectbox("Borough", boroughs)

# Map style
map_style = st.sidebar.selectbox(
    "Map Style",
    ["mapbox://styles/mapbox/streets-v11", "mapbox://styles/mapbox/satellite-v9"]
)

# Layer toggles
st.sidebar.header("Layers")
for layer in st.session_state.layer_states:
    st.session_state.layer_states[layer] = st.sidebar.checkbox(
        layer.replace("_", " ").title(),
        value=st.session_state.layer_states[layer]
    )

# Generate mock data
@st.cache_data
def generate_mock_data():
    # Food truck locations
    np.random.seed(42)
    n_trucks = 100
    trucks = pd.DataFrame({
        'latitude': np.random.normal(40.7128, 0.1, n_trucks),
        'longitude': np.random.normal(-74.0060, 0.1, n_trucks),
        'name': [f"Food Truck #{i}" for i in range(n_trucks)],
        'rating': np.random.uniform(3.0, 5.0, n_trucks),
        'cuisine': np.random.choice(['Mexican', 'Italian', 'American', 'Asian', 'Mediterranean'], n_trucks)
    })
    
    # Pedestrian activity
    n_pedestrians = 1000
    pedestrians = pd.DataFrame({
        'latitude': np.random.normal(40.7128, 0.15, n_pedestrians),
        'longitude': np.random.normal(-74.0060, 0.15, n_pedestrians),
        'count': np.random.exponential(100, n_pedestrians)
    })
    
    return trucks, pedestrians

trucks_df, pedestrians_df = generate_mock_data()

# Layout
col1, col2 = st.columns([7, 3])

with col1:
    # Create map layers
    layers = []
    
    if st.session_state.layer_states["food_trucks"]:
        food_trucks_layer = pdk.Layer(
            'ScatterplotLayer',
            data=trucks_df,
            get_position=['longitude', 'latitude'],
            get_color=[255, 0, 0, 160],
            get_radius=50,
            pickable=True,
            opacity=0.8,
        )
        layers.append(food_trucks_layer)

    if st.session_state.layer_states["pedestrians"]:
        heatmap_layer = pdk.Layer(
            'HeatmapLayer',
            data=pedestrians_df,
            get_position=['longitude', 'latitude'],
            get_weight='count',
            pickable=False,
            opacity=0.4,
        )
        layers.append(heatmap_layer)

    # Map view
    view_state = pdk.ViewState(
        latitude=40.7128,
        longitude=-74.0060,
        zoom=11,
        pitch=0
    )

    # Render map
    st.pydeck_chart(pdk.Deck(
        map_style=map_style,
        initial_view_state=view_state,
        layers=layers,
        tooltip={
            "html": "<b>Food Truck:</b> {name}<br/><b>Cuisine:</b> {cuisine}<br/><b>Rating:</b> {rating}/5.0",
            "style": {
                "backgroundColor": "steelblue",
                "color": "white"
            }
        }
    ))

with col2:
    # Stats panel
    st.header("Statistics")
    
    # Food truck stats
    st.subheader("Food Trucks")
    st.metric("Total Food Trucks", len(trucks_df))
    
    # Cuisine distribution
    fig = px.pie(trucks_df, names='cuisine', title='Cuisine Distribution')
    st.plotly_chart(fig, use_container_width=True)
    
    # Rating distribution
    fig = px.histogram(trucks_df, x='rating', nbins=20, title='Rating Distribution')
    st.plotly_chart(fig, use_container_width=True)
    
    # Pedestrian activity
    st.subheader("Pedestrian Activity")
    st.metric("Total Pedestrian Count", int(pedestrians_df['count'].sum()))
    
# Footer
st.markdown("---")
st.markdown("Data is simulated for demonstration purposes.")