Update app.py

app.py

@@ -11,7 +11,7 @@ import numpy as np
 def load_sample_data():
     data = {
         "Date": pd.date_range(start="2023-01-01", periods=100, freq="D"),
-        "Location": np.random.choice(["New York", "Los Angeles", "Chicago", "Houston", "Phoenix"], size=100),
+        "Location": np.random.choice(["Karachi", "Lahore", "Islamabad", "Peshawar", "Quetta"], size=100),
         "AQI": np.random.randint(50, 200, size=100),  # Random AQI values
         "Temperature": np.random.uniform(20, 35, size=100),
         "Humidity": np.random.uniform(30, 80, size=100),
@@ -68,19 +68,4 @@ st.markdown(
 # Sidebar inputs
 st.sidebar.header("Input Parameters")
 location = st.sidebar.selectbox("Select Location", data["Location"].unique())
-temperature = st.sidebar.slider("Temperature (°C)", 20, 40, 25)
-humidity = st.sidebar.slider("Humidity (%)", 30, 90, 50)
-
-# Prediction
-st.subheader("Predicted AQI")
-prediction = predict_aqi(model, temperature, humidity)
-st.write(f"The predicted AQI for {location} is: {prediction}")
-
-# Historical trends visualization
-st.subheader("Historical Data Trends")
-trends_image = plot_trends(data, location)
-st.image(trends_image)
-
-# Model performance
-st.sidebar.subheader("Model Performance")
-st.sidebar.write(f"Mean Squared Error: {mse:.2f}")
+temperature = st.sidebar.slider("Temperature (°C)", 20, 40,