import streamlit as st import pandas as pd import joblib from PIL import Image st.set_page_config(layout="wide") header = st.container() dataset = st.container() recommendation = st.container() with header: header_ = '

MOVIE RECOMMENDATION

' st.markdown(header_, unsafe_allow_html=True) text0 = '

With this application, we would like to make a list of movies that you will love watching!

' st.markdown(text0, unsafe_allow_html=True) with dataset: st.header('WE BRING TO YOU THE BEST MOVIE COLLECTION') col1, col2, col3 , col4, col5 = dataset.columns(5) logo_netflix = Image.open('source/image_streamlit/netflix.jpg') logo_amazon_prime = Image.open('source/image_streamlit/primevideo.png') logo_apple_tv = Image.open('source/image_streamlit/apple_tv.png') logo_hbo = Image.open('source/image_streamlit/HBO.jpg') logo_disney = Image.open('source/image_streamlit/disney.png') logo_paramount = Image.open('source/image_streamlit/paramount.png') with col1: st.image(logo_netflix) st.image(logo_hbo) with col3: st.image(logo_amazon_prime) st.image(logo_apple_tv) with col5: st.image(logo_paramount) st.image(logo_disney) with recommendation: st.header('LET US MAKE RECOMMENDATION TO YOU') text1 = '

Now you show us one of your favorite movies ...

' st.markdown(text1, unsafe_allow_html=True) text2 = '

... then let we recommend you movies that you will love!

' st.markdown(text2, unsafe_allow_html=True) frame = joblib.load('source/model/pickle_frame.joblib') st.write('### **SELECT** or **TYPE** here below the movie title you loved watching:') movie_chosen = st.selectbox('', options=[title for title in frame.columns.sort_values()]) st.write('### **Your favourite movie chosen:**') st.subheader(movie_chosen) st.write('### **Here are movies that we recommend you:**', unsafe_allow_html=True) recommendation_list = list(frame[movie_chosen].sort_values(ascending=False)[1:11].index.values) title = '' for i in recommendation_list: title += "- " + i + "\n" st.markdown(title)