app.py

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import binom

# Streamlit App Title
st.title("Binomial Distribution Visualizer 📊")

# Sidebar controls
N = st.slider("Number of trials (N)", min_value=1, max_value=100, value=10)
p = st.slider("Probability of success (p)", min_value=0.01, max_value=1.0, value=0.5, step=0.01)

# Compute binomial probabilities
x = np.arange(0, N + 1)
y = binom.pmf(x, N, p)

# Plot
fig, ax = plt.subplots()
ax.bar(x, y, color="skyblue", edgecolor="black")
ax.set_xlabel("Number of Successes")
ax.set_ylabel("Probability Mass Function")
ax.set_title(f"Binomial Distribution (N={N}, p={p})")

# Show plot
st.pyplot(fig)

# Display Summary
st.write(f"**Expected value (Mean)** = {N*p:.2f}")
st.write(f"**Variance** = {N*p*(1-p):.2f}")