Code Editor for app.py

import streamlit as st
import pydeck as pdk
import pandas as pd
import numpy as np
from datetime import datetime, timedelta

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

# Generate mock data
@st.cache_data
def generate_mock_data():
    # Food truck locations around NYC
    n_trucks = 100
    trucks_df = pd.DataFrame({
        'latitude': np.random.normal(40.7128, 0.05, n_trucks),
        'longitude': np.random.normal(-74.0060, 0.05, 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),
        'borough': np.random.choice(['Manhattan', 'Brooklyn', 'Queens', 'Bronx', 'Staten Island'], n_trucks)
    })

    # Pedestrian activity (heatmap)
    n_points = 1000
    heatmap_df = pd.DataFrame({
        'latitude': np.random.normal(40.7128, 0.1, n_points),
        'longitude': np.random.normal(-74.0060, 0.1, n_points),
        'weight': np.random.exponential(1, n_points)
    })

    return trucks_df, heatmap_df

# Load data
trucks_df, heatmap_df = generate_mock_data()

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

# Time slider
time_range = st.sidebar.slider(
    "Time Range",
    min_value=datetime(2023, 1, 1),
    max_value=datetime(2023, 12, 31),
    value=(datetime(2023, 6, 1), datetime(2023, 6, 30)),
    format="MM/DD/YY"
)

# Borough filter
selected_boroughs = st.sidebar.multiselect(
    "Filter by Borough",
    options=['Manhattan', 'Brooklyn', 'Queens', 'Bronx', 'Staten Island'],
    default=['Manhattan', 'Brooklyn']
)

# Layer toggles
st.sidebar.subheader("Map Layers")
show_trucks = st.sidebar.checkbox("Show Food Trucks", True)
show_heatmap = st.sidebar.checkbox("Show Pedestrian Heatmap", True)

# Map style
map_style = st.sidebar.selectbox(
    "Map Style",
    ["mapbox://styles/mapbox/streets-v11", 
     "mapbox://styles/mapbox/satellite-v9",
     "mapbox://styles/mapbox/dark-v10"]
)

# Heatmap settings
st.sidebar.subheader("Heatmap Settings")
radius = st.sidebar.slider("Heatmap Radius", 20, 100, 50)
intensity = st.sidebar.slider("Heatmap Intensity", 1, 10, 5)

# Filter data based on selections
filtered_trucks = trucks_df[trucks_df['borough'].isin(selected_boroughs)]

# Create map layers
layers = []

if show_trucks:
    trucks_layer = pdk.Layer(
        "ScatterplotLayer",
        filtered_trucks,
        get_position=['longitude', 'latitude'],
        get_color=[255, 0, 0, 160],
        get_radius=50,
        pickable=True
    )
    layers.append(trucks_layer)

if show_heatmap:
    heatmap_layer = pdk.Layer(
        "HeatmapLayer",
        heatmap_df,
        get_position=['longitude', 'latitude'],
        get_weight='weight',
        radiusPixels=radius,
        intensity=intensity,
        threshold=0.05
    )
    layers.append(heatmap_layer)

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

# Main content
st.title("NYC Interactive Map")

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

with col1:
    # Render the 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:.1f}⭐<br/>"
                   "<b>Borough:</b> {borough}",
            "style": {
                "backgroundColor": "white",
                "color": "black"
            }
        }
    ))

with col2:
    # Stats panel
    st.subheader("Statistics")
    
    # Food truck stats
    st.write("Food Trucks:")
    st.write(f"Total trucks: {len(filtered_trucks)}")
    
    # Average rating by borough
    st.write("\nAverage Rating by Borough:")
    borough_stats = filtered_trucks.groupby('borough')['rating'].mean().round(2)
    st.dataframe(borough_stats)
    
    # Cuisine distribution
    st.write("\nCuisine Distribution:")
    cuisine_dist = filtered_trucks['cuisine'].value_counts()
    st.bar_chart(cuisine_dist)