import streamlit as st
import pandas as pd
import pickle
import numpy as np
import sklearn

st.title("titanic prediction apps")

pclass=st.radio("pclass",[1,2,3])
sex=st.pills("gender",["male","female"])
age=st.slider("age", min_value=1, max_value=120)
sibsp=st.selectbox("sibsp",[0, 1, 2, 4, 3, 5, 8])
parch=st.selectbox("parch",[0, 1, 2, 5, 4, 3, 6])
fare=st.slider("fare", min_value=0, max_value=1000)
embarked=st.selectbox("embarked",["S","C","Q"])

inputss=pd.DataFrame(np.array([[pclass, sex, age, sibsp, parch, fare, embarked]]),columns=['pclass', 'sex', 'age', 'sibsp', 'parch', 'fare', 'embarked'])

pre_proce=pickle.load(open("pre_process","rb"))
model=pickle.load(open('model','rb'))

if st.button("Submit"):
    answers=model.predict(pre_proce.transform(inputss))[0]
    if answers==0:
        st.write("the person didnt survived")
    else:
        st.write("the person survived")
else:
    st.write("not able to predict")