Update app.py

app.py

@@ -1,53 +1,93 @@
 import joblib
 import pandas as pd
-import streamlit as st 
+import streamlit as st
 
 
-model = joblib.load('model.joblib')
-unique_values = joblib.load('unique_values.joblib')
-    
-unique_Married_Single =  unique_values["Married/Single"]
-unique_House_Ownership =  unique_values["House_Ownership"]
-unique_Car_Ownership =  unique_values["Car_Ownership"]
-unique_Profession =  unique_values["Profession"]
-unique_CITY =  unique_values["CITY"]
-unique_STATE =  unique_values["STATE"]
+model = joblib.load('model (1).joblib')
+unique_values = joblib.load('unique_values (1).joblib')
+
+unique_map =  unique_values["map"]
+unique_player=  unique_values["player"]
 
 
 def main():
-    st.title("Loan Risk_Flag Analysis")
+    st.title("agent Analysis")
 
     with st.form("questionaire"):
-        Income = st.slider("Income", min_value=10000, max_value=9999999)
-        Age = st.slider("Age", min_value=10, max_value=100)
-        Experience = st.slider("Experience", min_value=0, max_value=20)
-        CURRENT_JOB_YRS = st.slider("CURRENT_JOB_YRS", min_value=0, max_value=14)
-        CURRENT_HOUSE_YRS = st.slider("CURRENT_HOUSE_YRS", min_value=10, max_value=14)
-
-        Married_Single = st.selectbox("Married/Single", unique_Married_Single)
-        House_Ownership = st.selectbox("House_Ownership", unique_House_Ownership)
-        Car_Ownership = st.selectbox("Car_Ownership", unique_Car_Ownership)
-        Profession = st.selectbox("Profession", unique_Profession)
-        CITY = st.selectbox("CITY", unique_CITY)
-        STATE = st.selectbox("STATE", unique_STATE)
-        
-        
-
-        clicked = st.form_submit_button("Predict Risk_Flag")
+        rating= st.slider("rating", min_value=0.01, max_value=2.5)
+        acs= st.slider("acs", min_value=35, max_value=450)
+        kill = st.slider("kill", min_value=0, max_value=50)
+        death = st.slider("death", min_value=0, max_value=40)
+        assist = st.slider("assist", min_value=0, max_value=40)
+        kast% = st.slider("kast%", min_value=10, max_value=100)
+        adr = st.slider("adr", min_value=20, max_value=300)
+        hs% = st.slider("hs%", min_value=0, max_value=75)
+        fk = st.slider("fk", min_value=0, max_value=15)
+        fd = st.slider("fd", min_value=0, max_value=15)
+
+        map = st.selectbox("map", unique_map)
+        player = st.selectbox("player", unique_player)
+
+
+        clicked = st.form_submit_button("Predict agent")
         if clicked:
-            result=model.predict(pd.DataFrame({"Income": [Income],
-                                               "Age": [Age],
-                                               "Experience": [Experience],
-                                               "Married/Single": [Married_Single],
-                                               "House_Ownership": [House_Ownership],
-                                               "Car_Ownership": [Car_Ownership],
-                                               "Profession": [Profession],
-                                               "CITY": [CITY],
-                                               "STATE": [STATE],
-                                               "CURRENT_JOB_YRS": [CURRENT_JOB_YRS],
-                                               "CURRENT_HOUSE_YRS": [CURRENT_HOUSE_YRS]}))
-            result = 'none_risk_flag' if result[0] == 1 else 'risk_flag'
-            st.success('The predicted is {}'.format(result))
+            result=model.predict(pd.DataFrame({"map": [map],
+                                               "player": [player],
+                                               "rating": [rating],
+                                               "acs": [acs],
+                                               "kill": [kill],
+                                               "death": [death],
+                                               "assist": [assist],
+                                               "kast%": [kast%],
+                                               "adr": [adr],
+                                               "hs%": [hs%],
+                                               "fk": [fk],
+                                               "fd": [fd]}))
+            
+            if result[0] == 18:
+                result = 'sova'
+            elif result[0] == 10:
+                result = 'killjoy'
+            elif result[0] == 8:
+                result = 'jett'
+            elif result[0] == 9:
+                result = 'kayo'
+            elif result[0] == 12:
+                result = 'omen'
+            elif result[0] == 19:
+                result = 'viper'
+            elif result[0] == 17:
+                result = 'skye'
+            elif result[0] == 7:
+                result = 'harbor'
+            elif result[0] == 5:
+                result = 'fade'
+            elif result[0] == 0:
+                result = 'astra'
+            elif result[0] == 1:
+                result = 'breach'
+            elif result[0] == 14:
+                result = 'raze'
+            elif result[0] == 13:
+                result = 'phoenix'
+            elif result[0] == 20:
+                result = 'yoru'
+            elif result[0] == 4:
+                result = 'cypher'
+            elif result[0] == 16:
+                result = 'sage'
+            elif result[0] == 2:
+                result = 'brimstone'
+            elif result[0] == 11:
+                result = 'neon'
+            elif result[0] == 6:
+                result = 'gekko'
+            elif result[0] == 15:
+                result = 'reyna'
+            elif result[0] == 3:
+                result = 'chamber'
+
+            st.success('The predicted agent is {}'.format(result))
 
 if __name__=='__main__':
-    main()
+    main()