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import streamlit as st
import numpy as np
import random
# Streamlit app layout
st.title("Analyzing two sets of data")
with st.form("my_form"):
N = st.number_input("How many data points do you want for each set?", step=1)
# Button to generate the data
if st.form_submit_button("Generate Data"):
# Generate two sets of random data points
set1 = np.random.normal(loc=10, scale=2, size=N)
set2 = np.random.normal(loc=12, scale=3, size=N)
# Display the sets in the app
# st.write('Set 1:', set1)
# st.write('Set 2:', set2)
if "set1" in globals():
mean_set1 = np.mean(set1)
mean_set2 = np.mean(set2)
st.subheader("Means")
st.write(f"Mean of Set 1: {mean_set1:.2f}")
st.write(f"Mean of Set 2: {mean_set2:.2f}")
var_set1 = np.var(set1)
var_set2 = np.var(set2)
st.subheader("Variances")
st.write(f"Variance of Set 1: {var_set1:.2f}")
st.write(f"Variance of Set 2: {var_set2:.2f}")
cov_set = np.cov(set1, set2)[0, 1]
st.subheader("Covariance")
st.write(f"Covariance between Set 1 and Set 2: {cov_set:.2f}")
# Plotting
st.subheader("Scatter Plot")
st.write("Scatter plot of Set 1 against Set 2")
st.write("You can visualize the relationship between the two sets")
st.write("Note: This plot requires 'matplotlib' which may not be supported in all Streamlit deployment environments.")
st.write("If the plot is not visible, please run the code locally.")
st.pyplot(plt.scatter(set1, set2))
else:
st.write(":red[Please specify the number of data points]")
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