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 

def run(): 
    # membaut title
    st.title('Fifta 2022 Player Rating Prediction')

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

    # Tambahkan gambar
    image = Image.open('bola.jpg')
    st.image(image, caption = 'FIFA 2022')

    # Menambahkan deskripsi
    st.write('Page ini dibuat oleh Hammam')

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

    # Show dataframe
    df=pd.read_csv('https://raw.githubusercontent.com/FTDS-learning-materials/phase-1/master/w1/P1W1D1PM%20-%20Machine%20Learning%20Problem%20Framing.csv')
    st.dataframe(df)

    # Membuat bar plot

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


    # Membuat histogram

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

    # Membuat histogram berdasarkan inputan user

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

    # Membuat plotly plot

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

if __name__ == '__main__':
    run()