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Market_Basket_Analysis.py

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+import streamlit as st
+import pandas as pd
+from mlxtend.frequent_patterns import apriori
+from mlxtend.frequent_patterns import association_rules
+
+# Load initial data
+data = pd.read_csv("data.csv")
+# Load item images
+item_images = {
+    'Onion': 'https://m.media-amazon.com/images/I/71GUFttn0jL._AC_UF1000,1000_QL80_.jpg',
+    'Potato': 'https://m.media-amazon.com/images/I/61yXL70-RaL._AC_UF1000,1000_QL80_.jpg',
+    'Burger': 'https://img.freepik.com/free-photo/front-view-tasty-meat-burger-with-cheese-salad-dark-background_140725-89597.jpg',
+    'Milk': 'https://www.heritagefoods.in/blog/wp-content/uploads/2020/12/shutterstock_539045662.jpg',
+    'Beer': 'https://cdn.pixabay.com/photo/2017/06/24/23/41/beer-2439237_640.jpg',
+    'Eggs': 'https://img.freepik.com/free-photo/brown-eggs_2829-13455.jpg',
+    'Bread': 'https://thumbs.dreamstime.com/b/bread-cut-14027607.jpg',
+    'Cheese': 'https://t3.ftcdn.net/jpg/05/66/02/98/360_F_566029808_X7praimuCQt0MsLCmw5d65Pp5KqmTS8e.jpg',
+    'Tomato': 'https://upload.wikimedia.org/wikipedia/commons/thumb/8/89/Tomato_je.jpg/1231px-Tomato_je.jpg',
+    'Chicken': 'https://assets.epicurious.com/photos/62f16ed5fe4be95d5a460eed/1:1/w_4318,h_4318,c_limit/RoastChicken_RECIPE_080420_37993.jpg',
+    'Rice': 'https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRbfzh6ANLy74mq6aBFMC0P9BWFsiMH8Di0HuZouSSj5Q&s',
+    'Cereal': 'https://t4.ftcdn.net/jpg/00/60/08/87/360_F_60088763_3CVRHjk4Mn75y6kraCsSqNKEZkuf9032.jpg',
+    'Yogurt': 'https://www.shutterstock.com/image-photo/sour-cream-yogurt-wooden-bowl-260nw-1333497695.jpg',
+    'Apples': 'https://www.shutterstock.com/image-photo/red-apple-isolated-on-white-600nw-1727544364.jpg'
+}
+
+# Function to append new customer basket items to original data
+def append_customer_basket(items):
+    global data
+    last_id = data['ID'].max()
+    if pd.isna(last_id):  # If there's no previous data
+        last_id = 0
+    new_row = {item: 0 for item in data.columns[1:]}  # Initialize with 0s
+    new_row['ID'] = last_id + 1
+    for item in items:
+        if item in new_row:  # Check if item exists in data columns
+            new_row[item] = 1
+    data = data.append(new_row, ignore_index=True)
+    data.to_csv("data.csv", index=False)
+
+# Function to find items with highest lift or confidence
+def items_with_metric(rules, metric, n=10):
+    sorted_rules = rules.sort_values(by=metric, ascending=False)
+    return sorted_rules.head(n)
+
+# Sidebar option for company view
+st.sidebar.write('<h2 style="color: #ff6666;">Company View</h2>', unsafe_allow_html=True)
+st.sidebar.markdown('Enter new customer basket items:')
+new_onion = st.sidebar.checkbox('Onion')
+new_potato = st.sidebar.checkbox('Potato')
+new_burger = st.sidebar.checkbox('Burger')
+new_milk = st.sidebar.checkbox('Milk')
+new_beer = st.sidebar.checkbox('Beer')
+new_eggs = st.sidebar.checkbox('Eggs')
+new_bread = st.sidebar.checkbox('Bread')
+new_cheese = st.sidebar.checkbox('Cheese')
+new_tomato = st.sidebar.checkbox('Tomato')
+new_chicken = st.sidebar.checkbox('Chicken')
+new_rice = st.sidebar.checkbox('Rice')
+new_cereal = st.sidebar.checkbox('Cereal')
+new_yogurt = st.sidebar.checkbox('Yogurt')
+new_apples = st.sidebar.checkbox('Apples')
+
+if st.sidebar.button('Add Items'):
+    new_items = [item for item, new in zip(data.columns[1:], [new_onion, new_potato, new_burger, new_milk, new_beer, new_eggs, new_bread, new_cheese, new_tomato, new_chicken, new_rice, new_cereal, new_yogurt, new_apples]) if new]
+    append_customer_basket(new_items)
+    st.sidebar.success('New customer basket items added successfully!')
+
+# Perform market basket analysis
+frequent_itemsets = apriori(data.drop(columns=['ID']), min_support=0.2, use_colnames=True)
+rules = association_rules(frequent_itemsets, metric='lift', min_threshold=1)
+
+# Radio button to select metric
+selected_metric = st.sidebar.radio("Select Metric:", ('lift', 'confidence'))
+# Display items with highest lift in customer view
+st.markdown('<h1 style="color: #66ccff;">Exclusive Offers</h1>' if selected_metric == 'lift' else '<h1 style="color: #66ccff;">Your Fav Combo Awaits! Grab Exciting Offers Now!</h1>', unsafe_allow_html=True)
+items_displayed = set()  # To avoid duplicate pairs
+
+item2 = ""
+for index, row in items_with_metric(rules, selected_metric).iterrows():
+    if list(row['antecedents'])[0] != item2:
+        item1 = list(row['antecedents'])[0]
+        item2 = list(row['consequents'])[0]
+        # Check if the pair is already displayed or its reverse is displayed
+        if (item1, item2) not in items_displayed and (item2, item1) not in items_displayed:
+            col1, col2, col3 = st.columns(3)
+            with col1:
+                st.image(item_images[item1], caption=item1, width=150)
+            with col2:
+                st.markdown('<h1 style="color: #66ccff;">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;+</h1>', unsafe_allow_html=True)
+            with col3:
+                st.image(item_images[item2], caption=item2, width=150)
+
+
+        if selected_metric == 'lift':
+            if row['lift'] > 1.2:
+                if st.button(f"Weekly Offer: 20% off on purchase of {item1} and {item2}", key=f"{item1}_{item2}", help='Weekly Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+            elif row['lift'] > 1:
+                if st.button(f"Daily Offer: 15% off on purchase of {item1} and {item2}", key=f"{item1}_{item2}", help='Daily Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+            else:
+                if st.button(f"Festival Offer: Buy {item1} get {item2} free", key=f"{item1}_{item2}", help='Festival Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+        else:  # Confidence
+            if row['confidence'] > 0.7:
+                if st.button(f"High Confidence Offer: 25% off on purchase of {item1} and {item2}", key=f"{item1}_{item2}", help='High Confidence Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+            elif row['confidence'] > 0.5:
+                if st.button(f"Medium Confidence Offer: 15% off on purchase of {item1} and {item2}", key=f"{item1}_{item2}", help='Medium Confidence Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+            else:
+                if st.button(f"Low Confidence Offer: Buy {item1} get {item2} free", key=f"{item1}_{item2}", help='Low Confidence Offer'):
+                    pass
+                st.markdown('<style>div.stButton > button{background-color: #00FF00; color: black;}</style>', unsafe_allow_html=True)
+
+
+    # items_displayed.add((item1, item2))  # Add the pair to displayed items
+    
+
+company_password = "MYCOMPANY@123"
+
+# Sidebar option for viewing association rules separately
+view_rules = st.sidebar.checkbox('View Association Rules (Protected)')
+
+if view_rules:
+    # Create an empty slot for password input
+    password_input = st.sidebar.text_input("Enter Company Password", type="password")
+
+    # Display association rules and download option if password is correct
+    if st.sidebar.button("Submit") and password_input == company_password:
+        st.sidebar.markdown('<h1 style="color: #66ccff;">Association Rules</h1>', unsafe_allow_html=True)
+        # st.table(rules)
+        st.sidebar.markdown('<a href="data:text/csv;charset=utf-8,%EF%BB%BF' + rules.to_csv(index=False).encode('utf-8').decode().replace('\n', '%0A') + '" download="association_rules.csv" target="_blank">Download Association Rules</a>', unsafe_allow_html=True)
+    elif password_input != "":
+        st.sidebar.error("Incorrect password. Please try again.")
+

data.csv

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+ID,Onion,Potato,Burger,Milk,Beer,Eggs,Bread,Cheese,Tomato,Chicken,Rice,Cereal,Yogurt,Apples
+1,0,0,0,0,0,1,1,1,0,1,0,0,1,0
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+5,1,0,1,1,1,1,0,1,1,1,1,1,0,0
+6,0,0,1,0,1,1,1,0,0,0,1,1,1,1
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+8,1,1,0,0,0,0,0,0,1,0,1,0,0,0
+9,0,1,1,1,1,0,0,1,0,1,0,0,0,1
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requirements.txt

@@ -0,0 +1,3 @@
+mlxtend==0.23.1
+pandas==2.0.3
+streamlit==1.29.0