import streamlit as st
import pandas as pd
import pydeck as pdk

# Define the list of dictionaries with hospital information
hospital_list = [
    {
        'bed_count': 2766,
        'name': 'New York-Presbyterian Hospital',
        'city': 'New York',
        'state': 'NY',
        'latitude': 40.8404,
        'longitude': -73.9508,
        'zip': '10032'
    },
    {
        'bed_count': 2145,
        'name': 'Florida Hospital Orlando',
        'city': 'Orlando',
        'state': 'FL',
        'latitude': 28.5536,
        'longitude': -81.3568,
        'zip': '32803'
    },
    {
        'bed_count': 2020,
        'name': 'Jackson Memorial Hospital',
        'city': 'Miami',
        'state': 'FL',
        'latitude': 25.7893,
        'longitude': -80.2124,
        'zip': '33136'
    },
    {
        'bed_count': 1997,
        'name': 'Keck Medical Center of USC',
        'city': 'Los Angeles',
        'state': 'CA',
        'latitude': 34.0522,
        'longitude': -118.2437,
        'zip': '90033'
    },
    {
        'bed_count': 1956,
        'name': 'Montefiore Medical Center',
        'city': 'Bronx',
        'state': 'NY',
        'latitude': 40.8471,
        'longitude': -73.8816,
        'zip': '10467'
    },
    {
        'bed_count': 1926,
        'name': 'Rush University Medical Center',
        'city': 'Chicago',
        'state': 'IL',
        'latitude': 41.8745,
        'longitude': -87.6676,
        'zip': '60612'
    },
    {
        'bed_count': 1918,
        'name': 'University of Michigan Hospitals-Michigan Medicine',
        'city': 'Ann Arbor',
        'state': 'MI',
        'latitude': 42.2814,
        'longitude': -83.7483,
        'zip': '48109'
    },
    {
        'bed_count': 1863,
        'name': 'Parkland Health and Hospital System',
        'city': 'Dallas',
        'state': 'TX',
        'latitude': 32.7767,
        'longitude': -96.7970,
        'zip': '75235'
    },
    {
        'bed_count': 1858,
        'name': 'Houston Methodist Hospital',
        'city': 'Houston',
        'state': 'TX',
        'latitude': 29.7181,
        'longitude': -95.4044,
        'zip': '77030'
    },
    {
        'bed_count': 1800,
        'name': 'Brigham and Women\'s Hospital',
        'city': 'Boston',
        'state': 'MA',
        'latitude': 42.3367,
        'longitude': -71.1075,
        'zip': '02115'
    },
    {
        'bed_count': 1771,
        'name': 'Cleveland Clinic',
        'city': 'Cleveland',
        'state': 'OH',
        'latitude': 41.5047,    'longitude': -81.6218,
    'zip': '44195'
    },
    {
        'bed_count': 1730,
        'name': 'The Mount Sinai Hospital',
        'city': 'New York',
        'state': 'NY',
        'latitude': 40.7909,
        'longitude': -73.9524,
        'zip': '10029'
    },
    {
        'bed_count': 1729,
        'name': 'Northwestern Memorial Hospital',
        'city': 'Chicago',
        'state': 'IL',
        'latitude': 41.8953,
        'longitude': -87.6251,
        'zip': '60611'
    },
    {
        'bed_count': 1660,
        'name': 'Hospitals of the University of Pennsylvania-Penn Presbyterian',
        'city': 'Philadelphia',
        'state': 'PA',
        'latitude': 39.9526,
        'longitude': -75.1652,
        'zip': '19104'
    },
    {
        'bed_count': 1642,
        'name': 'Johns Hopkins Hospital',
        'city': 'Baltimore',
        'state': 'MD',
        'latitude': 39.2967,
        'longitude': -76.5913,
        'zip': '21287'
    },
    {
        'bed_count': 1614,
        'name': 'Cedars-Sinai Medical Center',
        'city': 'Los Angeles',
        'state': 'CA',
        'latitude': 34.0762,
        'longitude': -118.3882,
        'zip': '90048'
    },
    {
        'bed_count': 1577,
        'name': 'Massachusetts General Hospital',
        'city': 'Boston',
        'state': 'MA',
        'latitude': 42.3639,
        'longitude': -71.0711,
        'zip': '02114'
    },
    {
        'bed_count': 1566,
        'name': 'NYU Langone Hospitals',
        'city': 'New York',
        'state': 'NY',
        'latitude': 40.7429,
        'longitude': -73.9750,
        'zip': '10016'
    },
    {
        'bed_count': 1547,
        'name': 'Mayo Clinic Hospital-Rochester',
        'city': 'Rochester',
        'state': 'MN',
        'latitude': 44.0121,
        'longitude': -92.4802,
        'zip': '55902'
    },
    {
        'bed_count': 1537,
        'name': 'Stanford Health Care-Stanford Hospital',
        'city': 'Stanford',
        'state': 'CA',
        'latitude': 37.4354,
        'longitude': -122.1777,
        'zip': '94305'
    }
]




# Create a pandas dataframe from the hospital list
df = pd.DataFrame(hospital_list)

# Define the Pydeck layer
layer = pdk.Layer(
    'ScatterplotLayer',
    data=df,
    get_position='[longitude, latitude]',
    get_radius='bed_count/10',
    get_fill_color='[bed_count, 0, 255-bed_count]',
    get_line_color=[255, 255, 255],
    pickable=True
)

# Define the tooltip
tooltip = {
    'html': '<b>{name}</b><br/>{bed_count} beds<br/>{city}, {state} {zip}',
    'style': {
        'backgroundColor': 'white',
        'color': 'black'
    }
}

# Define the Pydeck map
deck = pdk.Deck(
    map_style='mapbox://styles/mapbox/light-v9',
    initial_view_state=pdk.ViewState(
        latitude=37.0902,
        longitude=-95.7129,
        zoom=3,
        pitch=0
    ),
    layers=[layer],
    tooltip=tooltip
)

# Render the map using st.pydeck_chart
st.pydeck_chart(deck)