Update app.py

app.py

@@ -2,6 +2,8 @@ import streamlit as st
 import numpy as np
 import pickle
 import streamlit.components.v1 as components
+from sklearn.preprocessing import LabelEncoder
+le = LabelEncoder()
 
 # Load the pickled model
 def load_model():
@@ -11,6 +13,10 @@ def load_model():
 def model_prediction(model, features):
     predicted = str(model.predict(features)[0])
     return predicted
+    
+def transform(text):
+    text = le.fit_transform(text)
+    return text[0]
 
 def app_design():
     # Add input fields for High, Open, and Low values
@@ -27,20 +33,29 @@ def app_design():
     elif Gender == 'Female':
           Gender = 0      
     Age = st.number_input("Age")
-    Industry = st.number_input("Industry")
-    Profession = st.number_input("Profession")
-    Traffic = st.number_input("Traffic")
-    Coach = st.number_input("Coach")
+    Industry = st.text_input("Industry")
+    Industry=transform([Industry])
+    Profession = st.text_input("Profession")
+    Profession=transform([Profession])
+    Traffic = st.text_input("Traffic")
+    Traffic=transform([Traffic])
+    Coach = st.selectbox('Coach',('Yes','No'))
+    if Coach == 'Yes':
+          Coach = 1
+    elif Coach == 'No':
+          Coach = 0 
     Head_gender = st.selectbox("Head Gender",('Male','Female'))
     if Head_gender == 'Male':
           Head_gender = 0
     elif Head_gender == 'Female':
           Head_gender = 1  
-    Greywage = st.number_input("Greywage")
-    Way = st.number_input("Way")
+    Greywage = st.text_input("Greywage")
+    Greywage=transform([Greywage])
+    Way = st.text_input("Way")
+    Way=transform([Way])
     Extraversion = st.number_input("Extraversion")
     Independ = st.number_input("Independ")
-    Selfcontrol = st.number_input("Selfcontrol")
+    Selfcontrol = st.number_input("Self-control")
     Anxiety = st.number_input("Anxiety")
     Novator = st.number_input("Novator")