add feature TelkomselProactive

app.py

@@ -2,13 +2,16 @@ import streamlit as st
 
 import eda
 import predictor
+import proactive
 
 navigation = st.sidebar.selectbox(
     label='Pilih Halaman',
-    options=('EDA', 'Predictor')
+    options=('EDA', 'Predictor', 'Proactive')
 )
 
 if navigation == 'EDA':
     eda.run()
 elif navigation == 'Predictor':
-    predictor.run()
+    predictor.run()
+elif navigation == 'Proactive':
+    proactive.run()

config.ini

@@ -1,8 +1,8 @@
 [DEFAULT]
-production = True
+production = False
 
 [DEVELOPMENT]
-URL = http://127.0.0.1:5000/predic
+URL = http://127.0.0.1:5000
 
 [PRODUCTION]
 URL = https://backend-telco-churn-kidfrom.koyeb.app

helpers/query.py

@@ -13,6 +13,15 @@ else:
 def fetch_all_data() -> pd.DataFrame:
     r = requests.get(URL+"/query")
     
+    if r.status_code == 200:
+        res = r.json()
+        return pd.DataFrame(res)
+    else:
+        return ('Error with status code ', str(r.status_code))
+    
+def proactive() -> pd.DataFrame:
+    r = requests.get(URL+"/proactive")
+    
     if r.status_code == 200:
         res = r.json()
         return pd.DataFrame(res)

proactive.py

@@ -0,0 +1,28 @@
+import streamlit as st
+
+from helpers import query
+
+def run():
+    st.title('TelkomselProactive')
+    
+    st.write("Duly noted: The data set is not real.")
+    
+    st.markdown(
+        """
+        Telkomsel employee can use this page to get a list of customer that is going to churn.
+        
+        By having this list, Telkomsel will be able to proactively go to the customer, that is about to churn, and prevent that said customer from opting out of the Telco services.
+        
+        The list is generated with this logic:
+        1. We don't have the future data set (the ones without Churn column).
+        2. So just imagine that the data set we are using is connected to the database. Thus, we use the latest data.
+        3. The back end fetch 10 sample and will predict whether a customer will churn or not.
+        4. The back end will only return the list of customer that will churn.
+        """
+    )
+    
+    if st.button(label='Fetch new list'):
+        df = query.proactive()
+        st.dataframe(df)
+    
+