Update app.py

app.py

@@ -55,7 +55,7 @@ user_type = st.radio("Are you a new user or an existing user?", ('New User', 'Ex
 if user_type == 'New User':
     # User input for new users
     new_user_age = st.slider("Age:", min_value=12, max_value=89, value=25)
-    new_user_category = st.selectbox("What best describes you:", ['Student', 'Professor', 'Banker', 'Businessman', 'Programmer'])
+    new_user_category = st.selectbox("What best describes you:", ['Student', 'Professor', 'Banker', 'Businessman', 'Programmer', 'Other'])
     new_user_gender = st.radio("Gender:", ['Male', 'Female', 'Other'])
 
 # Button to get recommendations for new users
@@ -90,7 +90,7 @@ if user_type == 'New User':
                                       'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
                                       'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
                                       'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
-                                      'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark', 'link']]
+                                      'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark']]
     
         
         recommendations_table = recommendations_table.reset_index(drop=True)
@@ -133,7 +133,7 @@ elif user_type == 'Existing User':
                                       'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
                                       'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
                                       'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
-                                      'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark', 'link']]
+                                      'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark']]
 
             recommendations_table = recommendations_table.reset_index(drop=True)
             st.dataframe(recommendations_table)