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 st.set_page_config( page_title= 'FIFA 2022', layout='wide', initial_sidebar_state='expanded' ) hide_streamlit_style = """ """ st.markdown(hide_streamlit_style, unsafe_allow_html=True) def run(): st.title('Heart Failure Prediction') # st.subheader('Heart Failure Prediction Exploratory Data Analysis') # #Show Dataframe d = pd.read_csv('hotel_bookings.csv') fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(12, 10)) sns.histplot(data=d, x='lead_time', hue='hotel', multiple='stack', bins=20, ax=ax[0, 0], palette='Set1') axes[0, 0].set_title("Booking Behavior by Hotel Type (Lead Time)") sns.barplot(data=d, x='hotel', y='is_canceled', ax=ax[0, 1], palette='Set1') axes[0, 1].set_title("Cancellation Rate by Hotel Type") sns.countplot(data=d, x='booking_changes', hue='hotel', ax=ax[1, 0], palette='Set1') axes[1, 0].set_title("Booking Changes by Hotel Type") sns.countplot(data=d, x='hotel', ax=ax[1, 1], palette='Set1') axes[1, 1].set_title("Total Bookings by Hotel Type") plt.tight_layout() plt.show() # st.write('#### scatterplot berdasarkan Input User') # pilihan1 = st.selectbox('Pilih column : ', ('age', 'creatinine_phosphokinase','ejection_fraction', 'platelets','serum_creatinine', 'serum_sodium', 'time'),key=1) # pilihan2 = st.selectbox('Pilih column : ', ('age', 'creatinine_phosphokinase','ejection_fraction', 'platelets','serum_creatinine', 'serum_sodium', 'time'),key=2) # pilihan3 = st.selectbox('Pilih column : ', ('anaemia', 'diabetes','high_blood_pressure', 'sex','smoking', 'DEATH_EVENT'),key=3) # fig = plt.figure(figsize=(15, 5)) # sns.scatterplot(data=d,x=d[pilihan1],y=d[pilihan2],hue=d[pilihan3]) # st.pyplot(fig) if __name__ == '__main__': run()