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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]") | |