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():
@@ -12,6 +14,10 @@ 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():
     
     image = '29.png' 
@@ -22,7 +28,8 @@ def app_design():
     RD_Spend = st.number_input("RD Spend")
     Administration= st.number_input("Administration")
     Marketing_Spend= st.number_input("Marketing_Spend")
-    State= st.number_input("State")
+    State= st.text_input("State")
+    State = State.transform(["State"])
     
     # Create a feature list from the user inputs
     features = [[RD_Spend, Administration, Marketing_Spend, State]]