Code Editor for app.py

import streamlit as st
import numpy as np
import pandas as pd

st.title("Normal Distribution Scatter Plot")

# User inputs for mean and variance
mean = st.number_input("Enter the mean", value=0.0)
variance = st.number_input("Enter the variance", value=1.0, min_value=0.0)

# Standard deviation is square root of variance
std_dev = np.sqrt(variance)

# Generate random data from normal distribution
if st.button("Generate Plot"):
    # Generate 1000 points
    data = np.random.normal(mean, std_dev, 1000)
    
    # Create a DataFrame with x values (just indices) and y values (the normal distribution values)
    df = pd.DataFrame({
        'x': range(len(data)),
        'y': data
    })
    
    # Display summary statistics
    st.write("### Summary Statistics")
    st.write(f"Sample Mean: {np.mean(data):.2f}")
    st.write(f"Sample Variance: {np.var(data):.2f}")
    
    # Create scatter plot
    st.scatter_chart(
        data=df,
        x='x',
        y='y',
        size=20,
        color='#1f77b4'
    )
    
    st.write("""
    ### About the Plot
    - Each point represents a random value drawn from the normal distribution
    - The spread of points shows the distribution shape
    - More points cluster around the mean value
    - Points become sparser as they deviate from the mean
    """)