ChurnDefender / app.py
gilangw's picture
Upload app.py
0de4504
import streamlit as st
from streamlit_option_menu import option_menu
import home
import eda
import prediction
from PIL import Image
# navigation = st.sidebar.selectbox('Select Page :', ('EDA', 'Predict Credit Card Default'))
# if navigation == 'EDA':
# eda.runEDA()
# else:
# prediction.runPredictor()
# Set page title and icon
# st.set_page_config(page_title='Final Project', page_icon='⭐')
# Create sidebar navigation
# st.markdown(
# f"""
# <style>
# [data-testid="stSidebar"] {{
# background-image: url(https://raw.githubusercontent.com/FTDS-assignment-bay/main/assets/ChurnGuardian-Logo-Transparants.png);
# background-repeat: no-repeat;
# padding-top: 20px;
# background-position: 10px 50px;
# background-size: 310px 85px;
# }}
# </style>
# """,
# unsafe_allow_html=True,
# )
st.set_page_config(
page_title='Telco Customer Churn and Segmentation',
layout='centered', #wide
initial_sidebar_state='expanded'
)
# st.title('Telco Customer Churn and Segmentation')
# image = Image.open('images\logo_crop_clean.png')
# image = Image.open('images\logo_grey_clean.png')
col1, col2, col3 = st.columns([10, 1, 5])
image_url = 'https://raw.githubusercontent.com/FTDS-assignment-bay/p2-final-project-ftds-001-sby-group-001/main/images/logo_crop_clean.png'
# qr_url = 'https://raw.githubusercontent.com/FTDS-assignment-bay/p2-final-project-ftds-001-sby-group-001/main/images/qr_link.png'
col1.image(image_url, width=450)
# col2.write('')
# col3.image(qr_url, width=150)
st.write('# Customer Churn and Segmentation')
st.subheader('Predict churn and retain your customer!')
st.markdown('---')
selected = option_menu(None, ["About", "EDA", "Predict"],
icons=['house', 'file-earmark-bar-graph', 'search'],
menu_icon="cast", default_index=0, orientation="horizontal",
styles={
"icon": {"color": "orange", "font-size": "15px"},
"nav-link": {"font-size": "15px", "text-align": "left", "margin":"1px", "--hover-color": "#eee"},
"nav-link-selected": {"background-color": "grey"},
}
)
if selected == 'About':
home.run()
elif selected == 'EDA':
eda.run()
else:
prediction.run()
#streamlit run app.py