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


st.set_page_config(
    page_title = 'DEFAULT PAYMENT NEXT MONTH - EDA',
    layout='wide',
    initial_sidebar_state='expanded'
)

def run():
    #membuat title
    st.title('DEFAULT PAYMENT NEXT MONTH PREDICTION')
    
    
    #membuat subheader
    st.subheader('EDA untuk analisis dataset DEFAULT PAYMENT NEXT MONTH')
    
    #menambahkan gambar
    st.image('https://navi.com/blog/wp-content/uploads/2022/06/credit-card.jpg')
    caption= ('CREDIT CARD')  
    
    #menambahkan deskripsi
    st.write('# page ini dibuat oleh Salman Hamka De Qais')
        
    
    #membuat garis
    st.markdown('---')
    
    
    #magicsyntax
    '''
    pada page ini, penuis akan melakukan explorasi sederhana, dataset yang digunakan adalah dataset Credit card. dataset ini berasa dari bigquery.com.
    
    '''    
    
    #showdatabase
    df = pd.read_csv('P1G5_Set_1_salman_hamka.csv')
    st.dataframe(df)


    #membuat barplot
    fig = plt.figure(figsize=(6, 3))
    sns.countplot(x='education_level', data=df)
    plt.title('Distribution of Education Level')
    plt.xlabel('Education Level')
    plt.ylabel('Count')
    st.pyplot(fig)
    
    #membuat histogram
    fig = plt.figure(figsize=(6, 3))
    sns.histplot(df['age'], bins=30, kde=True)
    plt.title('Distribution of Age')
    plt.xlabel('Age')
    plt.ylabel('Frequency')
    st.pyplot(fig)
    
    
    #membuat plotly plot    
    fig = plt.figure(figsize=(6, 3))
    sns.scatterplot(x='limit_balance', y='bill_amt_1', data=df, hue='default_payment_next_month', palette='coolwarm')
    plt.title('Limit Balance vs Bill Amount for the First Month')
    plt.xlabel('Limit Balance')
    plt.ylabel('Bill Amount (Month 1)')
    plt.legend(title='Default Payment Next Month')
    st.pyplot(fig)
    
    # Pie Chart untuk Jenis Kelamin
    sex_counts = df['sex'].value_counts()
    fig = plt.figure(figsize=(6, 3))
    sex_counts.plot.pie(autopct='%1.1f%%', startangle=90, colors=sns.color_palette('pastel'))
    plt.title('Distribution of Sex')
    plt.ylabel('')
    st.pyplot(fig)
    
    # Scatter Plot untuk Hubungan antara Batas Kredit dan Jumlah Tagihan Bulan Pertama
    fig = plt.figure(figsize=(6, 3))
    sns.scatterplot(x='limit_balance', y='bill_amt_1', data=df, hue='default_payment_next_month', palette='coolwarm')
    plt.title('Limit Balance vs Bill Amount for the First Month')
    plt.xlabel('Limit Balance')
    plt.ylabel('Bill Amount (Month 1)')
    plt.legend(title='Default Payment Next Month')
    st.pyplot(fig)
      
        
if __name__ == '__main__':
    run()