pages/1_Data_Card_and_Data_collection.py

import os
import pandas as pd
import streamlit as st
from io import StringIO

# Persistent file path for the dataset
DATA_FILE_PATH = "consumer_electronics_sales_data.csv"

# Page Title
st.markdown("<h1 style='text-align:center; color:white;'>Electronics Sales Data Set</h1>", unsafe_allow_html=True)

# Function to load the dataset from the disk
def load_dataset():
    if os.path.exists(DATA_FILE_PATH):
        return pd.read_csv(DATA_FILE_PATH)
    else:
        return None

# Load or reload the dataset into session state if not already done
if "dataset" not in st.session_state:
    st.session_state["dataset"] = load_dataset()

# File uploader widget to upload a new dataset
uploaded_file = st.file_uploader("Choose a CSV file", type=["csv"])

if uploaded_file is not None:
    # Read the uploaded CSV file into a pandas DataFrame
    df = pd.read_csv(uploaded_file)

    # Save the dataset permanently to disk
    df.to_csv(DATA_FILE_PATH, index=False)

    # Update session state
    st.session_state["dataset"] = df

    # Display success message
    st.success(f"Dataset uploaded and saved permanently as {DATA_FILE_PATH}!")

# Access the dataset from session state
df = st.session_state.get("dataset")

if df is not None:
    st.subheader("Dataset Preview:")
    st.write(df, use_container_width=True)

    st.subheader("Info of the Dataset:")
    buffer = StringIO()
    df.info(buf=buffer)
    st.text(buffer.getvalue())

    st.subheader("Dataset Shape (Rows, Columns):")
    st.write(df.shape)

    st.markdown('''**Dataset :**

| **Feature**              | **Description**                                                    | **Example**                  |
|-------------------------|--------------------------------------------------------------------|------------------------------|
| **ProductID**            | Unique identifier for each product.                                | 12345                        |
| **ProductCategory**      | Category of the consumer electronics product.                      | Smartphones, Laptops         |
| **ProductBrand**         | Brand of the product.                                              | Apple, Samsung               |
| **ProductPrice**         | Price of the product (in dollars).                                 | 999.99                       |
| **CustomerAge**          | Age of the customer.                                               | 35                           |
| **CustomerGender**       | Gender of the customer (0 - Male, 1 - Female).                     | 1                            |
| **PurchaseFrequency**    | Average number of purchases per year.                              | 3                            |
| **CustomerSatisfaction** | Customer satisfaction rating (1 - 5).                              | 4                            |
| **PurchaseIntent**       | Target variable: Intent to purchase (classification target).       | 0 (No), 1 (Yes)              |
''')

    

else:
    st.info("No dataset found. Please upload a CSV file.")

# Define the URL of the background image (use your own image URL)
background_image_url = "https://cdn-uploads.huggingface.co/production/uploads/67441c51a784a9d15cb12871/xpoN_mbctlrQAgRU06EPt.jpeg"

# Apply custom CSS for the background image and overlay
st.markdown(
    f"""
    <style>
        .stApp {{
            background-image: url("{background_image_url}");
            background-size: cover;
            background-position: center;
            height: 100vh;
        }}
        
        /* Semi-transparent overlay */
        .stApp::before {{
            content: "";
            position: absolute;
            top: 0;
            left: 0;
            width: 100%;
            height: 100%;
            background: rgba(0, 0, 0, 0.4);
            z-index: -1;
        }}
        
        /* Styling the content to ensure text visibility */
        .stMarkdown {{
            color: white;
            font-size: 100px;
        }}
    </style>
    """, 
    unsafe_allow_html=True
)


if st.button("Previous ⏮️"):
    st.switch_page("pages/0_Problem-Statement_and_Aim.py")
if st.button("Next ⏭️"):
    st.switch_page("pages/2_Data_CLeaning_and_Preprocessing.py")