Changes made

Website/app.py

@@ -31,25 +31,19 @@ def main():
         unsafe_allow_html=True
     )
 
-    # Custom CSS to remove space between buttons and position logo, footer always at the bottom
+    # Custom CSS to style buttons, position logo, and footer
     st.markdown(
         """
         <style>
-        .stButton button {
-            margin: 0;
-            padding: 0px;
+        .stButton>button {
+            font-size: 10;
+            height: 100%;
             width: 100%;
-            font-size: 100px;
-            white-space: nowrap; // Prevents text from wrapping
-            overflow: hidden; // Keeps text from overflowing
-            text-overflow: ellipsis; // Adds an ellipsis if text overflows
-        }
-        .stColumn {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            padding: 0; // Adjusts padding to reduce space between columns
-            margin: 0; // Removes margin around columns
+            white-space: nowrap; /* Prevents text from wrapping */
+            overflow: hidden; /* Keeps text from overflowing */
+            text-overflow: ellipsis; /* Adds an ellipsis if text overflows */
+            margin-bottom: 0; /* Removes space between buttons */
+            padding: 1; /* Removes padding around buttons */
         }
         .top-right-logo {
             position: absolute;
@@ -73,11 +67,10 @@ def main():
     )
 
     # Create a single row of columns with equal width
-    cols = st.columns(9)  # Creates 8 equally spaced columns
+    cols = st.columns(8)  # Creates 8 equally spaced columns (one less for Home)
 
     # Dictionary to map button names to functions
     pages = {
-        'Home': home,
         'OCR': ocr_invoice,
         'Product Perishability': product_perishability,
         'Customer Inventory': cust_purchase_expected_expiry,
@@ -100,6 +93,8 @@ def main():
     # Display selected page
     if 'page' in st.session_state and st.session_state['page'] in pages:
         pages[st.session_state['page']]()
+    else:
+        home()
 
     # Copyright footer
     st.markdown(

Website/pages/OCR_invoice.py

@@ -97,6 +97,7 @@ def convert_file_to_data(file_path, mime_type):
 
 def ocr_invoice():
   # st.set_page_config(page_title= "INVOICE-INFO EXTRACTOR")
+  st.write("<br>", unsafe_allow_html=True) 
 
   st.header("Invoice Details Extraction using OCR")
   # input= st.text_input("Input Prompt: ", key= "input")
@@ -187,4 +188,4 @@ def ocr_invoice():
     }, inplace=True)
 
 
-    st.dataframe(df_products)
+    st.dataframe(df_products, use_container_width=True)

Website/pages/closest_supermarket.py

@@ -177,7 +177,7 @@ def reset_user_input():
     st.session_state.user_input = ''
 
 def filter_dataframe(df, query):
-    return df[df['product_name'].str.contains(query, case=False, na=False)]
+    return df[df['Product Name'].str.contains(query, case=False, na=False)]
 
 def button_clicked():
     # Create a button and store its state
@@ -186,6 +186,7 @@ def button_clicked():
     return None
 
 def closest_supermarket():
+    st.write("<br>", unsafe_allow_html=True) 
 
     # import data using pandas if needed
     # root_dir = os.path.abspath(os.path.join(os.getcwd()))
@@ -259,7 +260,7 @@ def closest_supermarket():
 
         with col1:
             st.write("Closest Supermarkets Data")
-            st.dataframe(df_closest_supermarkets)  # Display the dataframe in the first column
+            st.dataframe(df_closest_supermarkets, use_container_width=True)  # Display the dataframe in the first column
 
         with col2:
             st.write("Display Closest Supermarkets")
@@ -276,7 +277,7 @@ def closest_supermarket():
         if selected_market == "Show All":
             filtered_df = df_supermarkets.reset_index(drop=True)[['Store Name', 'Product Id', 'Product Name', 'Product Price', 'Quantity', 'Expiry Date']]
         else:
-            filtered_df = df_supermarkets.query('store_name == @selected_market').reset_index(drop=True)[['Product Id', 'Product Name', 'Product Price', 'Quantity', 'Expiry Date']]
+            filtered_df = df_supermarkets.query("`Store Name` == @selected_market").reset_index(drop=True)[['Product Id', 'Product Name', 'Product Price', 'Quantity', 'Expiry Date']]
         if user_query:
             filtered_df = filter_dataframe(filtered_df, user_query)
 

Website/pages/cust_purchase_expected_expiry.py

@@ -22,11 +22,13 @@ def cust_purchase_expected_expiry():
     parquet_file_path = os.path.join(root_dir,'data', 'formatted_zone', 'purchases_nearing_expiry')
 
     try:
-        st.write("## Estimation of Expected Expiry Date")
+        st.write("<br>", unsafe_allow_html=True) 
+        st.header("Estimation of Expected Expiry Date")
 
         col1, col2, col3,  col4, col5, col6 = st.columns(6)
         # Read the Parquet file into a DataFrame
         df = load_data(parquet_file_path)
+        df = df[df['score']==100]
 
         df = df[["customer_name", "product_name", "purchase_date", "expected_expiry_date"]]
         df['customer_name'] = df['customer_name'].str.strip()
@@ -82,7 +84,7 @@ def cust_purchase_expected_expiry():
         }, inplace=True)
 
         st.write("<br>", unsafe_allow_html=True)  
-        st.dataframe(df)
+        st.dataframe(df, use_container_width=True)
 
     except FileNotFoundError as e:
         st.error(f"File not found: {e}")

Website/pages/dynamic_pricing_streamlit.py

@@ -29,7 +29,7 @@
 # st.set_page_config(page_title="Dynamic Pricing", layout="wide")
 
 # Title of the Streamlit app
-st.title("Dynamic Pricing Model Results")
+st.title("Dynamic Pricing")
 
 # Specify the path to the GCS Parquet file
 platform_customer_pricing_data_path = 'gs://formatted_zone/platform_customer_pricing_data_output'
@@ -52,6 +52,7 @@ def load_data_from_gcs(filepath):
     return df
 
 def dynamic_pricing_streamlit():
+    st.write("<br>", unsafe_allow_html=True) 
     # # Load the data from the parquet file
     # @st.cache
     # def load_data(parquet_path):
@@ -66,7 +67,7 @@ def dynamic_pricing_streamlit():
     df['percentage_decrease'] = ((df['unit_price'] - df['dynamic_price']) / df['unit_price']) * 100
 
     # Display the DataFrame
-    st.write("## Dynamic Pricing")
+    st.header("Dynamic Pricing")
 
     # Enhanced Filtering
     st.write("### Advanced Filters")
@@ -111,7 +112,7 @@ def dynamic_pricing_streamlit():
       'selling_date': 'Selling Date'
     }, inplace=True)
 
-    st.write(filtered_df.describe())
+    st.write(filtered_df.describe(),use_container_width=True)
 
     # Key Metrics
     st.write("### Key Metrics")
@@ -157,9 +158,11 @@ def convert_df_to_csv(df):
     st.write("### Select Columns to Display")
     all_columns = filtered_df.columns.tolist()
     filtered_df = filtered_df[filtered_df['Score']==100]
+    all_columns = [col for col in all_columns if col not in ['product_in_avg_expiry_file','Score']]
     selected_columns = st.multiselect("Select Columns", all_columns, default=all_columns)
 
-    st.dataframe(filtered_df[selected_columns])
+
+    st.dataframe(filtered_df[selected_columns], use_container_width=True)
 
     # if __name__ == "__main__":
     #     st.write("Streamlit app is running. Adjust the sliders or filters to explore the data.")

Website/pages/food_recommender.py

@@ -111,9 +111,10 @@ def initialize():
 
 
 def food_recommender():
+    st.write("<br>", unsafe_allow_html=True) 
     processed_df = initialize()
 
-    st.title("Food Generator")
+    st.header("Recipe Recommendatioin")
 
     user_ingredients = st.text_input("Enter ingredients, separated by commas", "rice, tomatoes")
     ingredients_list = [ingredient.strip() for ingredient in user_ingredients.split(',')]

Website/pages/product_perishability.py

@@ -47,7 +47,8 @@ def load_data_from_gcs(filepath):
 
 def product_perishability():
     try:
-        st.write("## Perishability of Food Items")
+        st.write("<br>", unsafe_allow_html=True) 
+        st.header("Perishability of Food Items")
         col1, col2, col3,  col4, col5 = st.columns(5)
 
         estimated_avg_expiry_df = load_data_from_gcs(gcs_parquet_path)

Website/pages/sentiment_analysis.py

@@ -80,7 +80,8 @@ def display_reviews(df):
 
 def sentiment_analysis():
     # Streamlit App
-    st.title("Sentiment Analysis")
+    st.write("<br>", unsafe_allow_html=True) 
+    st.header("Sentiment Analysis")
 
     col1, col2, col3,  col4, col5, col6, col7, col8, col9 = st.columns(9)
 

Website/pages/time_series.py

@@ -48,7 +48,8 @@
 spark = SparkSession.builder.getOrCreate()
 
 def show_feature5():
-    st.header("TIME SERIES ANALYSIS")
+    st.write("<br>", unsafe_allow_html=True) 
+    st.header("Time Series Analysis")
 
     # Dropdown for selecting B2B or B2C
     option = st.selectbox("Select Business Type", ("C2C", "C2C with expected price", "C2C with dynamic pricing", "B2C"))