import streamlit as st
import pandas as pd
import os

# Set up the app's title and description
st.title("Hotel Data Analysis App")
st.markdown("""
Welcome to the **Hotel Data Analysis App**. This app is designed to help you analyze hotel datasets, perform feature engineering, and create predictive models. Use the sidebar to navigate through the pages.

### Features:
- Download the dataset for exploration.
- Perform exploratory data analysis (EDA) and feature engineering.
- Create and evaluate machine learning models.
- Conclude insights from the analysis.

### About the Data:
The dataset includes hotel-related information such as price, ratings, discounts, cashback, and categories. It is designed for understanding relationships between features and building predictive models.
""")

# File upload section
st.markdown("## Upload Your Dataset")
uploaded_file = st.file_uploader("Choose a CSV file", type="csv")

# Handle file upload and dataset processing
if uploaded_file is not None:
    try:
        # Read the uploaded CSV file
        sample_data = pd.read_csv(uploaded_file)
        df = pd.DataFrame(sample_data)
        
        # Display a preview of the dataset
        st.markdown("### Dataset Preview")
        st.dataframe(df.head())

        # Convert the dataset to CSV for download
        csv = df.to_csv(index=False).encode('utf-8')
        
        # Add a download button for the processed dataset
        st.markdown("### Download Processed Dataset")
        st.download_button(
            label="Download Sample Dataset",
            data=csv,
            file_name="hotel_data.csv",
            mime="text/csv"
        )
    except Exception as e:
        st.error(f"An error occurred while processing the file: {e}")
else:
    st.warning("Please upload a dataset to proceed.")