Create app.py

app.py

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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]")