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import streamlit as st |
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import pandas as pd |
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import seaborn as sns |
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import matplotlib.pyplot as plt |
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import plotly.express as px |
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from PIL import Image |
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st.set_page_config( |
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page_title = 'Predict Credit Card Default', |
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layout = 'wide', |
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initial_sidebar_state='expanded' |
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) |
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def run(): |
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st.title('Predict Credit Card') |
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st.subheader('EDA untuk analisis dataset default credit card') |
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st.image('https://image.cermati.com/v1536918930/kcqxfjxwseh5e6kyrrpv.jpg', |
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caption= 'CREDIT CARD') |
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st.write('This page is made by badriahnursakinah') |
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st.write('# Hello') |
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st.markdown('---') |
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''' |
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Pada page kali ini, penulis akan melakukan |
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eksplorasi sederhana untuk memprediksi kemungkinan default pada pembayaran kartu kredit |
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Dataset yg digunakan adalah dataset predict default payment next month |
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Dataset ini berasal dari website Big Query |
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''' |
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data = pd.read_csv('P1G5_Set_1_badriah_nursakinah.csv') |
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st.dataframe(data) |
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st.write('#### Plot education_level') |
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fig = plt.figure(figsize=(15,5)) |
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sns.countplot(x='education_level', data= data) |
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st.pyplot(fig) |
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st.write('### Histogram') |
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options = st.selectbox('Pilih kolom:', |
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('sex', |
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'education_level', 'marital_status', |
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'age')) |
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fig = plt.figure(figsize=(15,5)) |
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sns.histplot(data[options], bins=30,kde=True) |
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st.pyplot(fig) |
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st.write('#### Plotly Plot - limit_balance dengan Overall') |
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fig = px.scatter(data,x='limit_balance',y='default_payment_next_month', hover_data=['pay_0','pay_2','pay_3','pay_4','pay_5','pay_6',]) |
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st.plotly_chart(fig) |
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if __name__ == '__main__': |
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run() |
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