Update app.py

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 import numpy as np
 import pandas as pd
-from sklearn.preprocessing import StandardScaler
 from sklearn.metrics.pairwise import cosine_similarity
 
 movies_df = pd.read_csv("movies.csv")
@@ -16,22 +15,18 @@ def calculate_similarity_matrix(genre_df):
 
 similarity_matrix = calculate_similarity_matrix(genre_df)
 
-# def random_selection(movies):
-#     random_movies = movies['title'].sample(5)
-#     return random_movies
-
 movie = st.text_input("Search for movie")
 if 'random_movies' not in st.session_state:
     st.session_state['random_movies'] = movies_df['title'].sample(5)
 
 random_movies = st.session_state['random_movies']
-movie1,id = None,None
+movie1,id = None,0
 if not movie:
     for i,movie in enumerate(random_movies,0):
         if st.button(movie):
             movie1 = movie
             id = i
-            st.write(movie1)
+            st.write("Selected Movie:",movie1)
             movie_id = movies_df[movies_df['title'] == random_movies.iloc[id]].index
             similar_movies_idx = similarity_matrix[movie_id[0]].argsort()[::-1][1:6]
             similar_movies = movies_df['title'].iloc[similar_movies_idx]