Update app.py

app.py

@@ -9,7 +9,7 @@ import streamlit as st
 
 # Load dataset
 tips = sns.load_dataset("tips")
-tips["tip_pct"] = tips["tip"] / tips["total_bill"] * 100
+tips["tip_percentage"] = tips["tip"] / tips["total_bill"] * 100
 
 # User question
 st.title("💡 Do people tip more on certain days of the week?")
@@ -38,20 +38,20 @@ if selected_time != "All":
 
 
 # KPI: average tip percentage
-avg_tip = filtered["tip_pct"].mean()
+avg_tip = filtered["tip_percentage"].mean()
 st.metric("For selected days and time , Average Tip %", f"{avg_tip:.2f}%")
 
 # Visualization
 if not filtered.empty:
     plt.figure(figsize=(6,4))
-    sns.boxplot(x="day", y="tip_pct", data=filtered, order=all_days)
+    sns.boxplot(x="day", y="tip_percentage", data=filtered, order=all_days)
     plt.title("Tip Percentage by Day")
     st.pyplot(plt.gcf())
     plt.close()
     
     # Dynamic insight
-    best_day = filtered.groupby("day")["tip_pct"].mean().idxmax()
-    best_value = filtered.groupby("day")["tip_pct"].mean().max()
+    best_day = filtered.groupby("day")["tip_percentage"].mean().idxmax()
+    best_value = filtered.groupby("day")["tip_percentage"].mean().max()
     st.success(f"💡 Insight: On average, for {selected_time}, {best_day} has the highest tip percentage at {best_value:.2f}%")
 else:
     st.info("No data available for the selected filters.")