add passive filter

app.py

@@ -83,9 +83,12 @@ def display_heroes_from_df(df,display_cols=display_cols, show_df=True):
         st.write(f"***{df['name'].values[i]}*** - {df['speed'].values[i]} - {df['class'].values[i]}")
         st.write(f'Attack:{df["attack"].values[i]} -- Defence:{df["defense"].values[i]} -- Health:{df["health"].values[i]}')
         st.write(f"***{df['skill'].values[i]}***" )
+        st.write("\n**Special Skills**")
         st.write(df['effects'].values[i])
-        # for sp in df['effects'].values[i]:
-        #     st.write(sp)
+
+        if df['passives'].values[i] != 0 and df['passives'].values[i] != '0':
+            st.write("\n**Passives**")
+            st.write(df['passives'].values[i])
 
 #########################################
 ## Helper function for LB/CB stat analysis
@@ -145,7 +148,7 @@ def return_hero_stat(df0, hero_name, lb_choice="None", costume_choice="None"):
     
     display_cols_0 = ['image', 'name', 'color', 'star', 'class', 'speed',]
     display_cols_1 = [] # ['power', 'attack', 'defense', 'health', ] --> to be select base one LB/Costume choice
-    display_cols_2 = ['Aether Power', 'source', 'family', 'types', 'skill', 'effects']
+    display_cols_2 = ['Aether Power', 'source', 'family', 'types', 'skill', 'effects', 'passives']
 
     prefix = get_prefix(lb_choice, costume_choice)
 
@@ -210,6 +213,7 @@ if genre == ':rainbow[Heroes Explorer]':
     
             special_type_option = st.text_input(label="SpecialSkill Category", value="Hit 3")
             special_text_option = st.text_input(label="SpecialSkill Text", value="Dispel")
+            passive_text_option = st.text_input(label="Passive Text", value="")
     with col2:
         st.header("Stat Filters")
         st.write("Tips: put the **minimum** att/def/hp stat you want to filter heroes")
@@ -275,6 +279,9 @@ if genre == ':rainbow[Heroes Explorer]':
 
     if special_text_option != '':
         idx_all.append(filter_by_1col(df, 'effects', special_text_option, exact_flag=False))    
+
+    if passive_text_option != '':
+        idx_all.append(filter_by_1col(df, 'passives', passive_text_option, exact_flag=False))    
     
     #########################################