Create app.py

app.py

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+import gradio as gr
+import requests
+import pandas as pd
+import folium
+from folium import plugins
+import json
+from datetime import datetime, timedelta
+import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+
+class AirQualityMonitor:
+    def __init__(self):
+        self.base_url = "https://www.airnowapi.org/aq"
+        # You'll need to get an API key from https://docs.airnowapi.org/
+        self.api_key = "YOUR_API_KEY_HERE"  # Replace with actual API key
+        
+    def get_current_observations(self, state_code=None, bbox=None):
+        """Get current air quality observations"""
+        if not self.api_key or self.api_key == "YOUR_API_KEY_HERE":
+            # Return sample data for demo purposes
+            return self._get_sample_data()
+            
+        url = f"{self.base_url}/observation/zipCode/current/"
+        params = {
+            'format': 'application/json',
+            'API_KEY': self.api_key,
+            'distance': 100
+        }
+        
+        if state_code:
+            # Get observations for a specific state
+            params['zipCode'] = self._get_state_zip(state_code)
+        
+        try:
+            response = requests.get(url, params=params)
+            response.raise_for_status()
+            return response.json()
+        except Exception as e:
+            print(f"API Error: {e}")
+            return self._get_sample_data()
+    
+    def _get_state_zip(self, state_code):
+        """Get a representative zip code for a state"""
+        state_zips = {
+            'CA': '90210', 'NY': '10001', 'TX': '73301', 'FL': '33101',
+            'IL': '60601', 'PA': '19101', 'OH': '43215', 'GA': '30301',
+            'NC': '27601', 'MI': '48201', 'NJ': '07001', 'VA': '23219',
+            'WA': '98101', 'AZ': '85001', 'MA': '02101', 'TN': '37201',
+            'IN': '46201', 'MO': '63101', 'MD': '21201', 'WI': '53201'
+        }
+        return state_zips.get(state_code, '90210')
+    
+    def _get_sample_data(self):
+        """Return sample data for demonstration"""
+        return [
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "PST",
+                "ReportingArea": "Los Angeles-South Coast Air Basin",
+                "StateCode": "CA",
+                "Latitude": 34.0522,
+                "Longitude": -118.2437,
+                "ParameterName": "PM2.5",
+                "AQI": 65,
+                "Category": {"Number": 2, "Name": "Moderate"}
+            },
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "EST",
+                "ReportingArea": "New York",
+                "StateCode": "NY",
+                "Latitude": 40.7128,
+                "Longitude": -74.0060,
+                "ParameterName": "Ozone",
+                "AQI": 45,
+                "Category": {"Number": 1, "Name": "Good"}
+            },
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "CST",
+                "ReportingArea": "Chicago",
+                "StateCode": "IL",
+                "Latitude": 41.8781,
+                "Longitude": -87.6298,
+                "ParameterName": "PM2.5",
+                "AQI": 85,
+                "Category": {"Number": 3, "Name": "Unhealthy for Sensitive Groups"}
+            },
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "MST",
+                "ReportingArea": "Phoenix",
+                "StateCode": "AZ",
+                "Latitude": 33.4484,
+                "Longitude": -112.0740,
+                "ParameterName": "Ozone",
+                "AQI": 95,
+                "Category": {"Number": 3, "Name": "Unhealthy for Sensitive Groups"}
+            },
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "PST",
+                "ReportingArea": "Seattle",
+                "StateCode": "WA",
+                "Latitude": 47.6062,
+                "Longitude": -122.3321,
+                "ParameterName": "PM2.5",
+                "AQI": 25,
+                "Category": {"Number": 1, "Name": "Good"}
+            },
+            {
+                "DateObserved": "2025-06-29",
+                "HourObserved": 14,
+                "LocalTimeZone": "EST",
+                "ReportingArea": "Miami",
+                "StateCode": "FL",
+                "Latitude": 25.7617,
+                "Longitude": -80.1918,
+                "ParameterName": "Ozone",
+                "AQI": 55,
+                "Category": {"Number": 2, "Name": "Moderate"}
+            }
+        ]
+
+def get_aqi_color(aqi):
+    """Return color based on AQI value"""
+    if aqi <= 50:
+        return "#00E400"  # Green
+    elif aqi <= 100:
+        return "#FFFF00"  # Yellow
+    elif aqi <= 150:
+        return "#FF7E00"  # Orange
+    elif aqi <= 200:
+        return "#FF0000"  # Red
+    elif aqi <= 300:
+        return "#8F3F97"  # Purple
+    else:
+        return "#7E0023"  # Maroon
+
+def create_air_quality_map(data):
+    """Create an interactive map with air quality data"""
+    if not data:
+        # Create empty map centered on US
+        m = folium.Map(location=[39.8283, -98.5795], zoom_start=4)
+        folium.Marker(
+            [39.8283, -98.5795],
+            popup="No data available. Please add your AirNow API key.",
+            icon=folium.Icon(color='red')
+        ).add_to(m)
+        return m._repr_html_()
+    
+    # Calculate map center
+    lats = [float(station['Latitude']) for station in data]
+    lons = [float(station['Longitude']) for station in data]
+    center_lat = sum(lats) / len(lats)
+    center_lon = sum(lons) / len(lons)
+    
+    # Create map
+    m = folium.Map(location=[center_lat, center_lon], zoom_start=4)
+    
+    # Add markers for each monitoring station
+    for station in data:
+        lat = float(station['Latitude'])
+        lon = float(station['Longitude'])
+        aqi = station.get('AQI', 0)
+        parameter = station.get('ParameterName', 'Unknown')
+        area = station.get('ReportingArea', 'Unknown Area')
+        category = station.get('Category', {}).get('Name', 'Unknown')
+        
+        color = get_aqi_color(aqi)
+        
+        popup_html = f"""
+        <div style="width: 200px;">
+            <h4>{area}</h4>
+            <p><strong>AQI:</strong> {aqi}</p>
+            <p><strong>Parameter:</strong> {parameter}</p>
+            <p><strong>Category:</strong> {category}</p>
+            <p><strong>Date:</strong> {station.get('DateObserved', 'N/A')}</p>
+            <p><strong>Time:</strong> {station.get('HourObserved', 'N/A')}:00 {station.get('LocalTimeZone', '')}</p>
+        </div>
+        """
+        
+        folium.CircleMarker(
+            location=[lat, lon],
+            radius=8,
+            popup=folium.Popup(popup_html, max_width=250),
+            color='black',
+            weight=1,
+            fill=True,
+            fillColor=color,
+            fillOpacity=0.8,
+            tooltip=f"{area}: AQI {aqi}"
+        ).add_to(m)
+    
+    # Add legend
+    legend_html = '''
+    <div style="position: fixed; 
+                top: 10px; right: 10px; width: 160px; height: 140px; 
+                background-color: white; border:2px solid grey; z-index:9999; 
+                font-size:14px; padding: 10px">
+    <h4>AQI Legend</h4>
+    <p><i class="fa fa-circle" style="color:#00E400"></i> Good (0-50)</p>
+    <p><i class="fa fa-circle" style="color:#FFFF00"></i> Moderate (51-100)</p>
+    <p><i class="fa fa-circle" style="color:#FF7E00"></i> Unhealthy for Sensitive (101-150)</p>
+    <p><i class="fa fa-circle" style="color:#FF0000"></i> Unhealthy (151-200)</p>
+    <p><i class="fa fa-circle" style="color:#8F3F97"></i> Very Unhealthy (201-300)</p>
+    </div>
+    '''
+    m.get_root().html.add_child(folium.Element(legend_html))
+    
+    return m._repr_html_()
+
+def create_aqi_chart(data):
+    """Create a chart showing AQI levels by location"""
+    if not data:
+        return None
+    
+    df = pd.DataFrame(data)
+    df['AQI'] = pd.to_numeric(df['AQI'], errors='coerce')
+    
+    # Create bar chart
+    fig = px.bar(df, 
+                 x='ReportingArea', 
+                 y='AQI',
+                 color='AQI',
+                 color_continuous_scale='RdYlGn_r',
+                 title='Air Quality Index by Location',
+                 labels={'AQI': 'Air Quality Index', 'ReportingArea': 'Location'})
+    
+    fig.update_layout(xaxis_tickangle=-45, height=500)
+    fig.update_traces(hovertemplate='<b>%{x}</b><br>AQI: %{y}<extra></extra>')
+    
+    return fig
+
+def get_air_quality_summary(data):
+    """Generate a summary of air quality data"""
+    if not data:
+        return "No air quality data available."
+    
+    df = pd.DataFrame(data)
+    df['AQI'] = pd.to_numeric(df['AQI'], errors='coerce')
+    
+    total_stations = len(df)
+    avg_aqi = df['AQI'].mean()
+    max_aqi = df['AQI'].max()
+    min_aqi = df['AQI'].min()
+    
+    # Count by category
+    categories = df['Category'].apply(lambda x: x.get('Name', 'Unknown') if isinstance(x, dict) else 'Unknown')
+    category_counts = categories.value_counts()
+    
+    summary = f"""
+    ## Air Quality Summary
+    
+    **Total Monitoring Stations:** {total_stations}
+    **Average AQI:** {avg_aqi:.1f}
+    **Highest AQI:** {max_aqi}
+    **Lowest AQI:** {min_aqi}
+    
+    ### Air Quality Categories:
+    """
+    
+    for category, count in category_counts.items():
+        percentage = (count / total_stations) * 100
+        summary += f"- **{category}:** {count} stations ({percentage:.1f}%)\n"
+    
+    return summary
+
+def update_data():
+    """Main function to fetch and display air quality data"""
+    monitor = AirQualityMonitor()
+    data = monitor.get_current_observations()
+    
+    map_html = create_air_quality_map(data)
+    chart = create_aqi_chart(data)
+    summary = get_air_quality_summary(data)
+    
+    return map_html, chart, summary
+
+# Create Gradio interface
+with gr.Blocks(title="Air Quality Monitor", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🌬️ Real-Time Air Quality Monitor")
+    gr.Markdown("Monitor air quality data from NOAA/EPA AirNow stations across the United States")
+    
+    with gr.Row():
+        gr.Markdown("""
+        This application displays real-time air quality data from over 2,000 monitoring stations 
+        across the United States. The data includes Air Quality Index (AQI) values for various 
+        pollutants like PM2.5, PM10, Ozone, and more.
+        
+        **Note:** To access live data, you need to:
+        1. Get a free API key from [AirNow API](https://docs.airnowapi.org/)
+        2. Replace `YOUR_API_KEY_HERE` in the code with your actual API key
+        
+        Currently showing sample data for demonstration.
+        """)
+    
+    with gr.Row():
+        update_btn = gr.Button("🔄 Update Air Quality Data", variant="primary", size="lg")
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            map_output = gr.HTML(label="Air Quality Map")
+        with gr.Column(scale=1):
+            summary_output = gr.Markdown(label="Summary")
+    
+    with gr.Row():
+        chart_output = gr.Plot(label="AQI Chart")
+    
+    # Add information section
+    with gr.Row():
+        gr.Markdown("""
+        ## About Air Quality Index (AQI)
+        
+        The AQI is an index for reporting daily air quality. It tells you how clean or polluted your air is:
+        
+        - **Good (0-50)**: 🟢 Air quality is satisfactory
+        - **Moderate (51-100)**: 🟡 Acceptable for most people
+        - **Unhealthy for Sensitive Groups (101-150)**: 🟠 May cause problems for sensitive individuals
+        - **Unhealthy (151-200)**: 🔴 May cause health problems for everyone
+        - **Very Unhealthy (201-300)**: 🟣 Health alert for everyone
+        - **Hazardous (301+)**: 🟤 Health emergency
+        
+        **Data Source:** EPA AirNow - Real-time air quality observations from government monitoring stations
+        """)
+    
+    # Load initial data
+    demo.load(update_data, outputs=[map_output, chart_output, summary_output])
+    update_btn.click(update_data, outputs=[map_output, chart_output, summary_output])
+
+if __name__ == "__main__":
+    demo.launch()