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

# Melebarkan visualisasi untuk memaksmalkan browser
st.set_page_config(
    page_title='Heart Failure',
    layout='wide',
    initial_sidebar_state='expanded'
)

def run():
    # Membuat title
    st.title('Patients with Heart Failure-Death Prediction')

    # Menambahkan Gambar
    image = Image.open('heart.jpg')
    st.image(image, caption='Heart Failure')

    # Menambahkan Deskripsi
    st.write('## Definition')
    st.write('Heart failure is progressive condition in which the heart muscle is unable to pump enough blood to meet the body needs for blood and oxygen.' 
             'Basically, the heart cant keep up with its workload.'
             'Heart failure can caused by diabetes, smoking, and high of blood pressure.'
             'Heart failure can cause death in chronic and acute conditions.')

    st.write('## Heart and kidney')
    st.write('The interaction between the heart and kidney can often become deranged in heart failure.'
             'Not only do heart failure and chronic kidney disease (CKD) often co-exist and share common risk factors in their development, both heart and kidney disease can worsen each others prognosis.'
             'The preload of the heart directly depends on the sodium and water homeostasis regulated by the kidney.'
             'The kidney depends on adequate contraction and relaxation of the heart to have a sufficient trans-renal pressure gradient to maintain renal blood flow (RBF).'
             'So, heart failure have a correlation with sodium level in blood and creatinin (CPK enzyme).')

    # Membuat Garis Lurus
    st.markdown('---')

    # Membuat Sub Headrer
    st.subheader('EDA for Analyze Patients')

    # Magic Syntax
    '''
    On this page, the author will do a simple exploration.
    The dataset used is the Heart Failure dataset.
    This dataset comes from GCP in the Hacktiv8 project.
    '''

    # Show DataFrame
    df1 = pd.read_csv('h8dsft_P1G3_fadya_ulya.csv')
    st.dataframe(df1)

    # Membuat Barplot
    st.write('#### Plot Death Event')
    fig = plt.figure(figsize=(15,8))
    sns.countplot(x='DEATH_EVENT', data=df1, palette="PuRd")
    st.pyplot(fig)

    # Membuat Barplot Diabetes, Smoking, dan Darah Tinggi
    st.write('#### Diabetes')
    plt.figure(figsize=(15,8))
    sns.countplot(x='diabetes', data=df1, palette="Blues")
    st.pyplot(fig)

    st.write('#### High Blood Pressure')
    plt.figure(figsize=(15,8))
    sns.countplot(x='high_blood_pressure', data=df1, palette="Blues")
    st.pyplot(fig)

    st.write('#### Smoking')
    plt.figure(figsize=(15,8))
    sns.countplot(x='smoking', data=df1, palette="Blues")
    st.pyplot(fig)

    # Membuat Histogram Berdasarkan Input User
    st.write('#### Histogram Based On User Input')
    pilihan = st.selectbox('Choose Column : ', ('age', 'creatinine_phosphokinase', 'ejection_fraction', 
                                                'platelets', 'serum_sodium', 'serum_creatinine', 'time'))
    fig = plt.figure(figsize=(15,5))
    sns.histplot(df1[pilihan], bins=30, kde=True)
    st.pyplot(fig)

if __name__ == '__main__':
    run()