eda.py

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='FIFA 2022',
    layout = 'wide',
    initial_sidebar_state='expanded'
)

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

    # membuat sub header
    st.subheader ('EDA untuk Analisa Dataset FIFA 2022')

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

    # Menambahkan Deskripsi
    st.write('Page ini dibuat oleh')
    st.write('# Halo')


    # 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 barplot
    st.write('#### Plot AttackingWorkRate')
    fig =plt.figure(figsize=(15,5))
    sns.countplot(x='AttackingWorkRate',data=data)
    st.pyplot(fig)

    # Membuat histogram
    st.write('### Histogram of Rating')
    fig = plt.figure(figsize=(15,5))
    sns.histplot(data['Overall'],bins=30,kde=True)
    st.pyplot(fig)

    # Membuat Plotly Plot
    st.write('#### PlotlyPlots - ValueEUR dengan Overall')
    fig = px.scatter(data, x='ValueEUR', y='Overall',hover_data=['Name','Age'])
    st.plotly_chart(fig)

    # Membuat histogram berdasarkan input user
    st.write('### Histogram berdasarkan input user')
    pilihan = st.selectbox('Pilih column :',('Age','Weight','Height','ShootingTotal'))
    fig = plt.figure(figsize=(15,5))
    sns.histplot(data[pilihan],bins=30,kde=True)
    st.pyplot(fig)

if __name__ == '__main__':
    run()