Final Streamlit

.streamlit/config.toml

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+[theme]
+primaryColor="#033f63"
+backgroundColor="#28666e"
+secondaryBackgroundColor="#7c9885"
+textColor="#FFFFFF"
+font="sans serif"

Test.py

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+
+"""
+    Streamlit webserver-based Recommender Engine.
+    Author: Explore Data Science Academy.
+    Note:
+    ---------------------------------------------------------------------
+    Please follow the instructions provided within the README.md file
+    located within the root of this repository for guidance on how to use
+    this script correctly.
+    NB: !! Do not remove/modify the code delimited by dashes !!
+    This application is intended to be partly marked in an automated manner.
+    Altering delimited code may result in a mark of 0.
+    ---------------------------------------------------------------------
+    Description: This file is used to launch a minimal streamlit web
+	application. You are expected to extend certain aspects of this script
+    and its dependencies as part of your predict project.
+	For further help with the Streamlit framework, see:
+	https://docs.streamlit.io/en/latest/
+"""
+# Streamlit dependencies
+import streamlit as st
+
+# Data handling dependencies
+import pandas as pd
+import numpy as np
+import pickle
+from PIL import Image
+
+# Custom Libraries
+from utils.data_loader import load_movie_titles
+from recommenders.collaborative_based import collab_model
+from recommenders.content_based import content_model
+
+# Data Loading
+title_list = load_movie_titles('resources/data/movies.csv')
+
+# App declaration
+def main():
+
+    # DO NOT REMOVE the 'Recommender System' option below, however,
+    # you are welcome to add more options to enrich your app.
+    page_options = ["Recommender System","Solution Overview", "About Us",
+                   "Contact Us"]
+
+    # -------------------------------------------------------------------
+    # ----------- !! THIS CODE MUST NOT BE ALTERED !! -------------------
+    # -------------------------------------------------------------------
+    page_selection = st.sidebar.selectbox("Choose Option", page_options)
+    if page_selection == "Recommender System":
+        # Header contents
+        st.write('# Movie Recommender Engine')
+        st.write('### EXPLORE Data Science Academy Unsupervised Predict')
+        st.image('resources/imgs/Image_header.png',use_column_width=True)
+        # Recommender System algorithm selection
+        sys = st.radio("Select an algorithm",
+                       ('Content Based Filtering',
+                        'Collaborative Based Filtering'))
+
+        # User-based preferences
+        st.write('### Enter Your Three Favorite Movies')
+        movie_1 = st.selectbox('First Option',title_list[14930:15200])
+        movie_2 = st.selectbox('Second Option',title_list[25055:25255])
+        movie_3 = st.selectbox('Third Option',title_list[21100:21200])
+        fav_movies = [movie_1,movie_2,movie_3]
+
+        # Perform top-10 movie recommendation generation
+        if sys == 'Content Based Filtering':
+            if st.button("Recommend"):
+                try:
+                    with st.spinner('Crunching the numbers...'):
+                        top_recommendations = content_model(movie_list=fav_movies,
+                                                            top_n=10)
+                    st.title("We think you'll like:")
+                    for i,j in enumerate(top_recommendations):
+                        st.subheader(str(i+1)+'. '+j)
+                except:
+                    st.error("Oops! Looks like this algorithm does't work.\
+                              We'll need to fix it!")
+
+
+        if sys == 'Collaborative Based Filtering':
+            if st.button("Recommend"):
+                try:
+                    with st.spinner('Crunching the numbers...'):
+                        top_recommendations = collab_model(movie_list=fav_movies,
+                                                           top_n=10)
+                    st.title("We think you'll like:")
+                    for i,j in enumerate(top_recommendations):
+                        st.subheader(str(i+1)+'. '+j)
+                except:
+                    st.error("Oops! Looks like this algorithm does't work.\
+                              We'll need to fix it!")
+
+
+    # -------------------------------------------------------------------
+
+    # ------------- SAFE FOR ALTERING/EXTENSION -------------------
+    if page_selection == "Solution Overview":
+        st.title("Solution Overview")
+        st.write("This page describes the winning approach.")
+
+        def datasets():
+            st.markdown("### **_Datasets_**")
+            st.write("""
+            A snapshot of the data sets used in training and testing the model.
+                    """)
+            st.markdown("#### **_Train Data_**")
+            st.write(pd.DataFrame({"userId": [5163, 106343, 146790],
+                                  "movieId": [57669, 5, 5459],
+                                  "rating": [4.0, 4.5, 5.0],
+                                  "timestamp": [1518349992, 1206238739, 1076215539]}))
+
+            st.markdown("#### **_Test Data_**")
+            st.write(pd.DataFrame({"userId": [1, 1, 1],
+                                  "movieId": [2011, 4144, 5767]}))
+
+        def eda():
+            st.markdown("### **_Exploratory Data Analysis_**")
+            st.write("""
+            A summary of the insights in the movies data set.
+                    """)
+
+            # Reads in saved graphs
+            bar = """The bar chart describes the number of ratings in millions for each 
+            movie in the database scaled from a rating of 0.5 to 5.0. The lowest 
+            rated movies are given a 0.5 rating and the highest rated movies are
+            given a 4.0. On average the ratings are 3.0 and above indicating
+            that the users enjoy the movies in the data set."""
+
+            st.image('resources/imgs/Karabo.jpg', caption = bar,  use_column_width = True)
+
+            fig = """
+            The line chart describes a count of the number of ratings for each movie.
+            The shape of the chart indicates a negative relationship between the count
+            ratings and the number of movies. This means that a few movies have a 
+            higher count of ratings, and as the number of movies increase the count of
+            ratings decreases."""
+            st.image('resources/imgs/Karabo.jpg', caption = fig, use_column_width = True)
+
+        if st.sidebar.button("Datasets"):
+            datasets()
+        if st.sidebar.button("Exploratory Data Analysis"):
+            eda()
+
+    if page_selection == "About Us":
+        st.title("About Us Tendai")
+
+        def team():
+            st.markdown("### **_ Our Data Scientists_**")
+
+            siya = Image.open('resources/imgs/Karabo.jpg')
+            viwe = Image.open('resources/imgs/Karabo.jpg') 
+            mj = Image.open('resources/imgs/Karabo.jpg') 
+            tendi = Image.open('resources/imgs/Karabo.jpg')
+            b = Image.open('resources/imgs/Karabo.jpg')
+
+            st.image([siya, mj, tendi], 
+                     caption = ["Siyasanga", "MJ", "Tendani"],
+                     width = 150)
+            st.image([viwe, b], caption = ["Siviwe", "Bongani"],
+                     width = 150)
+
+            st.markdown("### **_ Learn more about Team_3_CPT_**")
+            st.write("""Like mystery, Siyasanga creates wonder and wonder is the basis of 
+                     her desire to understand.""")
+            st.write("""Free spirited and adaptable are the truest words that describe 
+                     Siviwe. A little something for rainbows and sunny skies to envy.""")
+            st.write("Optimism and hardwork is what drives MJ to become a data scientist.")
+            st.write("The most friendliest person alive... a simple guy and a simple motto.")
+            st.write(""""All I want is to be a real boy in front of a computer begging
+                    my program to run." - Bongani""")
+
+        def mission():
+            st.markdown("### **_Our Mission_**")
+            st.write("""
+            We are a creative and passionate group of data scientists who are
+            on a mission to make a difference in our community by bringing
+            innovative programs and projects that promote ingenuity, inclusivity
+            and integrity. We want to make our community a better place by 
+            giving people tools and information to make better decisions.""")
+
+        def statement():
+            st.markdown("### **_Problem Statement_**")
+            st.write("""
+            To construct a recommendation algorithm based on content or 
+            collaborative filtering, capable of accurately predicting how
+            a user will rate a movie they have not yet viewed based on their 
+            historical preferences.""")
+
+        def landscape():
+            st.markdown("### **_Problem Landscape_**")
+
+            st.image('resources/imgs/Karabo.jpg', use_column_width = True)
+            st.write("""
+            Providing an accurate and robust solution to this challenge has 
+            immense economic potential, with users of the system being 
+            exposed to content they would like to view or purchase - 
+            generating revenue and platform affinity.""")
+
+        def motivation():
+            st.markdown("### **_Motivation_**")
+            st.write("""Improve customer experience by exposing users to 
+            content that matches their taste.""")
+            st.write("""Increase sales for service providers.""")
+            st.write("""Reduce transaction costs of finding and selecting 
+            relevant content in an online platform.""")
+
+        if st.sidebar.button("Team"):
+            team()
+        if st.sidebar.button("Our Mission"):
+            mission()
+        if st.sidebar.button("Problem Statement"):
+            statement()
+        if st.sidebar.button("Problem Landscape"):
+            landscape()
+        if st.sidebar.button("Motivation"):
+            motivation()
+
+    if page_selection == "Contact Us":
+        st.title("Contact Us")
+        st.markdown("### **_Have any questions? We would love to hear from you._**")
+
+        st.text_input("""Name:""")
+        st.text_input("""Surname:""")
+        st.text_input("""Email:""")
+        st.text_area("""Comment:""")
+        st.button("""Submit""")
+
+        st.markdown("### **_Contact Info_**")
+        st.write("""Tel: 012 589 4856""")
+        st.write("""Fax: 012 589 4800""")
+        st.write("""Email: info@team3cpt.com""")
+        st.write("""Postal Address""")
+        st.write("""Private Bag X756, Observatory, Western Cape,
+                 South Africa""")
+
+        st.markdown("### **_Social Media_**")
+        st.write("""LinkedIn: Team_3_CPT""")
+        st.write("""Facebook: Team_3_CPT""")
+        st.write("""Instagram: @team_3_cpt""")
+        st.write("""Twitter: @team_3_cpt""")
+
+    # You may want to add more sections here for aspects such as an EDA,
+    # or to provide your business pitch.
+
+
+if __name__ == '__main__':
+    main()