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| import streamlit as st | |
| import pandas as pd | |
| import seaborn as sns | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| st.set_page_config( | |
| page_title='FIFA 2022 - EDA', | |
| layout='wide', | |
| initial_sidebar_state='expanded' | |
| ) | |
| def run(): | |
| # Title | |
| st.title('House Price Prediction by Area Characteristics') | |
| # Membuat Sub Header | |
| st.subheader('EDA untuk Analisa Dataset FIFA 2022') | |
| # Membuat Deskripsi | |
| st.write('Page ini dibuat oleh *Danu Purnomo*') | |
| # Menambahkan Gambar | |
| #image = Image.open('soccer.jpg') | |
| #st.image(image, caption='FIFA 2022') | |
| # Membuat Garis Lurus | |
| st.markdown('---') | |
| # Magic Syntax | |
| ''' | |
| Pada page kali ini, penulis akan melakukan eskplorasi sederhana. | |
| Dataset yang digunakan adalah dataset FIFA 2022. | |
| Dataset ini berasal dari web sofifa.com. | |
| ''' | |
| # 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 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) | |
| # Membuat Plotly Plot | |
| #st.write('#### Plotly Plot - ValueEUR dengan Overall') | |
| #fig = px.scatter(data, x='ValueEUR', y='Overall', hover_data=['Name', 'Age']) | |
| #st.plotly_chart(fig) | |
| if __name__ == '__main__': | |
| run() |