Update app.py

app.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import streamlit as st
 import plotly.graph_objects as go
- 
+
 # Sample AQI data (replace with your actual data source)
 data = {
     'Timestamp': pd.to_datetime(['2024-07-26 10:00:00', '2024-07-26 11:00:00', '2024-07-26 12:00:00', '2024-07-26 13:00:00', '2024-07-26 14:00:00']),
@@ -13,7 +13,7 @@ data = {
     'NO2': [15, 25, 30, 20, 12]
 }
 df = pd.DataFrame(data)
- 
+
 # AQI Categories and Health Recommendations
 aqi_categories = {
     (0, 50): {'label': 'Good', 'color': 'green', 'recommendations': {
@@ -59,10 +59,10 @@ aqi_categories = {
         'general': 'Health emergency: a health alert indicates that everyone may experience more serious health effects.'
     }}
 }
- 
+
 # Streamlit app
 st.title('Air Quality Dashboard')
- 
+
 # Current AQI and Category
 current_aqi = df['AQI'].iloc[-1]
 current_category = None
@@ -70,9 +70,13 @@ for aqi_range, category_data in aqi_categories.items():
     if aqi_range[0] <= current_aqi <= aqi_range[1]:
         current_category = category_data
         break
- 
-st.subheader(f"Current AQI: {current_aqi} ({current_category['label']})", color=current_category['color'])
- 
+
+# Display AQI with color
+st.markdown(
+    f"<h2 style='color: {current_category['color']}'>Current AQI: {current_aqi} ({current_category['label']})</h2>",
+    unsafe_allow_html=True
+)
+
 # Gauge chart for AQI
 fig_gauge = go.Figure(go.Indicator(
     mode="gauge+number",
@@ -90,20 +94,18 @@ fig_gauge = go.Figure(go.Indicator(
     }
 ))
 st.plotly_chart(fig_gauge)
- 
- 
+
 # Detailed Pollutant Levels
 st.subheader('Detailed Pollutant Levels')
 st.line_chart(df[['PM2.5', 'O3', 'CO', 'SO2', 'NO2']])
- 
+
 # Health Recommendations
 st.subheader('Health Recommendations')
- 
+
 st.write(f"**General:** {current_category['recommendations']['general']}")
 st.write(f"**Heart Patients:** {current_category['recommendations']['heart_patients']}")
 st.write(f"**Old Age:** {current_category['recommendations']['old_age']}")
 st.write(f"**Mid Age:** {current_category['recommendations']['mid_age']}")
 st.write(f"**Young Age:** {current_category['recommendations']['young_age']}")
- 
- 
-# Add more visualizations (e.g., bar charts for pollutant comparison) as needed.
+
+# Add more visualizations (e.g., bar charts for pollutant comparison) as needed.