import streamlit as st
import pandas as pd
import seaborn as sns 
import matplotlib.pyplot as plt
import plotly.express as px
from PIL import Image

st.set_page_config(
   page_title= 'Prediksi Serangan Jantung',
   layout='wide',
   initial_sidebar_state='expanded'
)

def run():
    image = Image.open('image.png')
    resized_image = image.resize((300, 300))
    st.image(resized_image, caption='Serangan jantung')

    st.title('Prediksi Serangan Jantung')
    df = pd.read_csv('https://raw.githubusercontent.com/Azrieldr/latihan/master/h8dsft_P1G3_Azrieldr.csv')
    st.dataframe(df)


    persentaseKematian = df['DEATH_EVENT'].mean()*100
    # Create pie chart
    fig, ax = plt.subplots(figsize=(10,15), dpi=100)
    ax.pie([persentaseKematian, 100-persentaseKematian], labels=['Meninggal', 'Selamat'], autopct='%1.1f%%')
    ax.set_title('Persentase angka kematian')
    st.pyplot(fig)

    jender = {0: 'Perempuan', 1: 'Laki Laki'}
    persentaseJender = df.replace({'sex': jender}).groupby('sex')['DEATH_EVENT'].mean()*100
    st.write('Persentase kematian per jender\n',persentaseJender)
    deathperjender= df.replace({'sex': jender}).groupby('sex')['DEATH_EVENT'].sum()
    st.write('Total kematian per jender',deathperjender)
    BP = {0: 'rendah-normal', 1: 'tinggi'}
    BPx = df.replace({'high_blood_pressure': BP}).groupby('high_blood_pressure')['DEATH_EVENT'].mean()*100
    st.write('Total kematian per jender',BPx)



if __name__== '__main__':
    run()