Update pages/Introduction.py

pages/Introduction.py

@@ -1,25 +1,48 @@
 import streamlit as st
 import pandas as pd
 
-# Introduction and About Data
-st.title("Introduction and About Data")
+# 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 helps analyze hotel datasets, perform feature engineering, 
-and create predictive models. Use the sidebar to navigate through the pages.
+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**:
+### 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.
+### 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.
 """)
 
-st.markdown("### Download the Dataset")
-sample_data = pd.read_csv(r"C:\Users\user\Downloads\agoda_data.csv")
-df = pd.DataFrame(sample_data)
-csv = df.to_csv(index=False).encode('utf-8')
-st.download_button("Download Sample Dataset", data=csv, file_name="hotel_data.csv", mime="text/csv")
+# 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.")