Update app.py

app.py

@@ -1,15 +1,12 @@
 import streamlit as st
 from datasets import load_dataset
-from collections import Counter
 
-# Load dataset and precompute MBTI type counts
+# Load dataset (not used for count anymore, but left in case needed later)
 @st.cache_resource
-def load_mbti_data_and_counts():
-    dataset = load_dataset("Shunian/kaggle-mbti-cleaned-augmented", split="train")
-    counts = Counter(example["label"] for example in dataset)
-    return dataset, counts
+def load_mbti_data():
+    return load_dataset("Shunian/kaggle-mbti-cleaned-augmented", split="train")
 
-mbti_data, mbti_counts = load_mbti_data_and_counts()
+mbti_data = load_mbti_data()
 
 # MBTI → Academic disciplines
 mbti_to_disciplines = {
@@ -62,14 +59,6 @@ if user_input:
 
     st.divider()
 
-    st.subheader("📊 How Common Is Your Type?")
-    count = mbti_counts.get(user_input, 0)
-    total = sum(mbti_counts.values())
-    percentage = (count / total) * 100 if total > 0 else 0
-    st.success(f"You're one of {count:,} people ({percentage:.2f}%) in the dataset with the {user_input} personality.")
-
-    st.divider()
-
     st.subheader("🎓 Recommended Academic Disciplines")
     for field in mbti_to_disciplines[user_input]:
         st.markdown(f"- {field}")