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import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
# Streamlit app layout
st.title("Random Sample Generator and Statistics Calculator")
with st.form("my_form"):
sample_size = st.number_input("Enter the sample size:", min_value=1, step=1, value=100)
low = st.number_input("Enter the lower bound of the uniform distribution:", value=0)
high = st.number_input("Enter the upper bound of the uniform distribution:", value=1)
if st.form_submit_button("Generate Samples"):
# Generate random samples
samples = np.random.uniform(low, high, sample_size)
# Display the generated samples
if "samples" in locals():
st.subheader("Generated Samples")
st.write(samples)
# Calculate and display descriptive statistics
st.subheader("Descriptive Statistics")
st.write(f"Mean: {np.mean(samples):.2f}")
st.write(f"Standard Deviation: {np.std(samples):.2f}")
st.write(f"Variance: {np.var(samples):.2f}")
st.write(f"Min: {np.min(samples):.2f}")
st.write(f"Max: {np.max(samples):.2f}")
# Visualize the distribution with a histogram
st.subheader("Histogram")
plt.hist(samples, bins=20, color='skyblue', edgecolor='black')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Histogram of Random Samples')
st.pyplot(plt)
plt.close()
else:
st.warning("Please generate samples first.")
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