predict_page.py

import streamlit as st
import pickle
import numpy as np

def load_model():
    with open('saved_steps.pkl','rb') as file:
        data=pickle.load(file)
    return data

data=load_model()

regressor=data["model"]
le_country=data["le_country"]
le_education=data["le_education"]

def show_predict_page():
    st.title("Software Developer Salary Prediction")

    st.write("""### We need some information to predict the salary""")


    countries = ("United States of America",
    "Germany",
    "United Kingdom of Great Britain and Northern Ireland",
    "Canada",
    "India",
    "France",
    "Netherlands",
    "Australia",
    "Brazil",
    "Spain",
    "Sweden",
    "Italy",
    "Poland",
    "Switzerland",
    "Denmark",
    "Norway",
    "Israel")

    education= ('Bachelor’s degree', 'Less than a Bachelors', 'Master’s degree',
        'Post grad')
    
    country=st.selectbox("Country",countries)
    education=st.selectbox("Education Level",education)

    experience=st.slider("Years of Experience",0,50,3)

    ok=st.button("Calculate Salary")
    if ok:
        X=np.array([[country,education,experience]])
        X[:,0]=le_country.transform(X[:,0])
        X[:,1]=le_education.transform(X[:,1])
        X=X.astype(float)

        salary=regressor.predict(X)
        st.subheader(f"The estimated salary is ${salary[0]:.2f}")