Update app.py

app.py

@@ -1,13 +1,12 @@
 import streamlit as st
 import pandas as pd
-import time
-import matplotlib.pyplot as plt
 import json
 
-# Load USMLE questions from a JSON file
+# Load USMLE questions from a JSON file (Replace this with your actual data)
 def load_questions():
-    return pd.DataFrame([{"question": "What is the serum level of X?", "answer": "High"},
-                         {"question": "What causes Y?", "answer": "Z"}])
+    return pd.DataFrame([{"question": "What is the serum level in Alzheimer's?", "answer": "High", "topic": "Alzheimers"},
+                         {"question": "What causes memory loss?", "answer": "Many factors", "topic": "Memory"},
+                         {"question": "How is cognitive behavior therapy used?", "answer": "For mental health", "topic": "cognitive"}])
 
 # Vote for a story
 def vote_story(index):
@@ -30,8 +29,15 @@ tab = st.selectbox("Choose a Tab", ["USMLE Questions", "Story Voting"])
 
 if tab == "USMLE Questions":
     questions_df = load_questions()
-    selected_q = st.selectbox('Select a question:', questions_df['question'])
-    st.write(f"Answer: {questions_df.loc[questions_df['question'] == selected_q, 'answer'].values[0]}")
+    
+    medical_keywords = ["Brain 🧠", "Memory 📔", "Alzheimers 🌀", "Cognitive 🤔", "Mental 💭", "Behavior 🎭"]
+    
+    for keyword in medical_keywords:
+        keyword_clean = keyword.split(" ")[0]
+        if st.button(keyword):
+            filtered_data = questions_df[questions_df['topic'].str.contains(keyword_clean, case=False)]
+            st.write(f"Filtered Dataset by '{keyword_clean}' 📊")
+            st.dataframe(filtered_data.iloc[:, :3])
 
 elif tab == "Story Voting":
     for index, row in st.session_state.df.iterrows():