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my_app_assignment.py

@@ -59,6 +59,8 @@ st.markdown("**Interpretation:** The scatter plot shows that as the total bill g
 # Plot 3 — Tip Percentage by Smoking Status
 fig3, ax3 = plt.subplots(figsize=(6,4))  # match Colab size
 sns.set_style("whitegrid")  # match Colab style
+
+# Use filtered data from sidebar
 sns.boxplot(x="smoker", y="tip_pct", data=filtered, palette="Set2", ax=ax3)
 
 # Titles and labels
@@ -70,12 +72,14 @@ ax3.grid(axis="y", linestyle="--", alpha=0.7)
 # Display plot in Streamlit
 st.pyplot(fig3)
 
-# Calculate medians dynamically
+# --- Calculate medians dynamically ---
 median_smokers = filtered[filtered["smoker"]=="Yes"]["tip_pct"].median()
 median_non_smokers = filtered[filtered["smoker"]=="No"]["tip_pct"].median()
 
-# Display interpretation
-st.markdown("**Interpretation:** The box plot and median values suggest that smoking status does not have a large impact on the average tip percentage. " \
-"The median tip percentage for smokers is 15,41%, and for non-smokers it is 15.56%." \
-" However, there are some instances where smokers gave significantly higher tips.")
-
+# --- Display interpretation dynamically ---
+st.markdown(
+    f"**Interpretation:** The median tip percentage for smokers is {median_smokers:.2f}%, "
+    f"and for non-smokers it is {median_non_smokers:.2f}%. "
+    "The box plot suggests that smoking status does not have a large impact on the average tip percentage. "
+    "However, there are some instances where smokers gave significantly higher tips."
+)