app.py

import pandas as pd
import streamlit as st
import numpy as np
import joblib
import warnings
warnings.filterwarnings("ignore")

model = joblib.load("model.pkl")
scaler = joblib.load("scaler.pkl")
col = joblib.load("columns.pkl")

st.set_page_config(page_title="Insurance charges prediction",page_icon="🪙")

st.title("Insurance charges prediction 📜💸")

age = st.slider("Age",17,100,50)
sex = st.selectbox("Gender",["female","male"])
bmi = st.slider("BMI",1.0,30.0,10.0)
chid = st.number_input("Children",0,10,2)
smo = st.selectbox("Smoker",["yes","no"])
reg = st.selectbox("Region",['southwest', 'southeast', 'northwest', 'northeast'])
# reg = st.selectbox("Region",[0,1])
bmi_cat = st.selectbox("BMI categor obese",[0,1])

if(sex == "female"):
    sex = 1
else:
    sex = 0
if(smo == "yes"):
    smo = 1
else:
    smo = 0
if(reg == "southeast"):
    reg = 1
else:
    reg = 0

if st.button("predic"):
    user_df = pd.DataFrame([{
        "age":age,
        "is_female":sex,
        "bmi":bmi,
        "children":chid,
        "is_smoker" :smo,
        "region_southeast":reg,
        "bmi_category_Obese":bmi_cat
    }]) 
    c = ["age","bmi","children"]
    user_df[c] = scaler.transform(user_df[c])
    prediction = model.predict(user_df)[0]
    pred = round(prediction,2)
    # print(prediction)
    st.success(f"Your insurance charges prediction is ₹ {pred}")