import streamlit as st
import seaborn as sns
import plotly.express as px
import matplotlib.pyplot as plt
from PIL import Image
import pandas as pd
st.set_page_config(layout='wide', page_title='FIFA 2022 EDA', initial_sidebar_state="expanded")

def run():
    # title
    st.title("FIFA 2022 Player Rating Prediction")

    # subheader
    st.subheader('EDA untuk Analysis dataset FIFA 2022')

    # add image
    image = Image.open('soccer.jpg')
    st.image(image, caption='FIFA 2022')

    # add description
    st.write('###### Page ini dibuat oleh **Ardi** sebagai bahan latihan')

    # membuat garis lurus
    st.markdown('---')

    # show dataframe
    data = pd.read_csv('https://raw.githubusercontent.com/ardhiraka/FSDS_Guidelines/master/p1/v3/w1/P1W1D1PM%20-%20Machine%20Learning%20Problem%20Framing.csv')
    st.dataframe(data)

    # membuat bar
    st.write('### Attacking Work Rate')
    fig = plt.figure(figsize=(15,6))
    sns.countplot(x='AttackingWorkRate', data=data)
    st.pyplot(fig)

    # membuat histogram
    st.write('### Overall Rating distribution')
    fig = plt.figure(figsize=(15,6))
    sns.histplot(data['Overall'], bins=30, kde=True)
    st.pyplot(fig)

    # membuat histogram dinamis
    st.write('### Histogram based on Input')
    kolom = st.selectbox('Pilih Kolom: ', ('Age','Weight', 'Height', 'ShootingTotal'))
    fig = plt.figure(figsize=(15, 7))
    sns.histplot(data[kolom], bins=30, kde=True)
    st.pyplot(fig)


    # membuat plotly plot
    st.write('### Plotly - Overall Rating vs ValueEUR')
    fig = px.scatter(data, x='ValueEUR', y='Overall', hover_data=['Name','Age'])
    st.plotly_chart(fig)

if __name__ == '__main__':
    run()