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import streamlit as st
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
from PIL import Image
st.set_page_config(
page_title = 'Home Credit Analysis - EDA',
layout = 'wide',
initial_sidebar_state = 'expanded'
)
def run():
# Membuat Title
st.title('Home Credit Analysis')
# Membuat Sub Header
st.subheader('EDA for Home Credit Analysis')
# Menambahkan Gambar
image = Image.open('credit.jpeg')
st.image(image, caption='Home Credit')
# Menambahkan Deskripsi
st.write('This page created by **Imam Zarkasie**')
st.write('### Hello!')
st.write('#### The competition of credit card service is heating up!')
st.write('##### In this page we can explore customer segmentation, more than that this website provides an ability to predict a customer payment risk.')
# Membuat Garis Lurus
st.markdown('---')
# Magic Syntax
'''
On this page, the author will do a simple exploration.
The dataset used is the churn dataset.
'''
# Show DataFrame
df = pd.read_csv('df_subset.csv')
st.dataframe(df)
#Melihat histogram fitur target
# Membuat visualisasi Distribusi Payment
fig, ax =plt.subplots(1,2,figsize=(15,6))
sns.countplot(x='TARGET', data=df, palette="winter", ax=ax[0])
ax[0].set_xlabel("Payment", fontsize= 12)
ax[0].set_ylabel("# of Payment", fontsize= 12)
fig.suptitle('Payment Distribution', fontsize=18, fontweight='bold')
ax[0].set_ylim(0,300000)
ax[0].tick_params(axis='x', rotation=90)
plt.xlabel("Payment", fontsize= 12)
plt.ylabel("# of Payment", fontsize= 12)
for p in ax[0].patches:
ax[0].annotate("%.0f"%(p.get_height()), (p.get_x() + p.get_width() / 2,
p.get_height()+205), ha='center', va='center',fontsize = 11)
df['TARGET'].value_counts().plot(kind='pie',autopct='%1.1f%%', textprops = {"fontsize":12})
ax[1].set_ylabel("% of Payment", fontsize= 12)
st.pyplot(fig)
# Membuat visualisasi Distribusi Contract
fig, ax =plt.subplots(1,2,figsize=(15,6))
sns.countplot(x='NAME_CONTRACT_TYPE', data=df, palette="winter", ax=ax[0])
ax[0].set_xlabel("Contract", fontsize= 12)
ax[0].set_ylabel("# of Contract", fontsize= 12)
fig.suptitle('Contract Distribution', fontsize=18, fontweight='bold')
ax[0].set_ylim(0,300000)
ax[0].tick_params(axis='x', rotation=90)
plt.xlabel("Contract", fontsize= 12)
plt.ylabel("# of Contract", fontsize= 12)
for p in ax[0].patches:
ax[0].annotate("%.0f"%(p.get_height()), (p.get_x() + p.get_width() / 2,
p.get_height()+205), ha='center', va='center',fontsize = 11)
df['NAME_CONTRACT_TYPE'].value_counts().plot(kind='pie',autopct='%1.1f%%', textprops = {"fontsize":12})
ax[1].set_ylabel("% of Contract", fontsize= 12)
plt.show()
# Menampilkan plot di Streamlit
st.pyplot(fig)
# Membuat visualisasi Distribusi Gender
fig, ax =plt.subplots(1,2,figsize=(15,6))
sns.countplot(x='CODE_GENDER', data=df, palette="winter", ax=ax[0])
ax[0].set_xlabel("Gender", fontsize= 12)
ax[0].set_ylabel("# of Gender", fontsize= 12)
fig.suptitle('Gender Distribution', fontsize=18, fontweight='bold')
ax[0].set_ylim(0,300000)
ax[0].tick_params(axis='x', rotation=90)
plt.xlabel("Gender", fontsize= 12)
plt.ylabel("# of Gender", fontsize= 12)
for p in ax[0].patches:
ax[0].annotate("%.0f"%(p.get_height()), (p.get_x() + p.get_width() / 2,
p.get_height()+205), ha='center', va='center',fontsize = 11)
df['CODE_GENDER'].value_counts().plot(kind='pie',autopct='%1.1f%%', textprops = {"fontsize":12})
ax[1].set_ylabel("% of Gender", fontsize= 12)
plt.show()
# Menampilkan plot di Streamlit
st.pyplot(fig)
# Membuat plot scatter
fig, ax = plt.subplots(figsize=(6, 3))
sns.scatterplot(x='AMT_ANNUITY', y='AMT_CREDIT', hue='TARGET', data=df, ax=ax)
# Menambahkan label sumbu dan judul plot
plt.xlabel('AMT_ANNUITY')
plt.ylabel('AMT_CREDIT')
plt.title('Scatter Plot: AMT_ANNUITY vs AMT_CREDIT')
# Menambahkan legenda
plt.legend(title='Target')
# Menampilkan plot di Streamlit
st.pyplot(fig)
if __name__=='__main__':
run() |