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
@@ -20,14 +26,20 @@ def app_design():
     st.subheader("Enter the following values:")
 
     Age = st.number_input("Age")
-    Workclass = st.number_input("Workclass")
+    Workclass = st.text_input("Workclass")
+    Wrokclass = transform([Workclass])
     Final_weight = st.number_input("Final_weight")
-    Education = st.number_input("Education")
+    Education = st.text_input("Education")
+    Education=transform([Education])
     Education_Num = st.number_input("Education_Num")
-    Marital_status = st.number_input("Marital_status")
-    Occupation = st.number_input("Occupation")
-    Relationship = st.number_input("Relationship")
-    Race = st.number_input("Race")
+    Marital_status = st.text_input("Marital_status")
+    Marital_status=transform([Marital_status])
+    Occupation = st.text_input("Occupation")
+    Occupation=transform([Occupation])
+    Relationship = st.text_input("Relationship")
+    Relationship=transform([Relationship])
+    Race = st.text_input("Race")
+    Race=transform([Race])
     Sex = st.selectbox("Sex",('Male','Female'))
     if Sex == 'Male':
         Sex = 1
@@ -36,7 +48,8 @@ def app_design():
     Capital_gain = st.number_input("Capital_gain")
     Capital_loss = st.number_input("Capital_loss")
     Hours_per_week = st.number_input("Hours_per_week")
-    Native_country = st.number_input("Native_country")
+    Native_country = st.text_input("Native_country")
+    Native_country=transform([Native_country])
     
  
     # Create a feature list from the user inputs