Update app.py

app.py

@@ -1,69 +1,72 @@
 import streamlit as st
 import pandas as pd
-import os
+import numpy as np
 
-# Load the default dataset or upload a new one
-@st.cache_data
-def load_default_dataset():
-    file_path = "consumer_electronics_sales_data.csv"
-    if os.path.exists(file_path):
-        return pd.read_csv(file_path)
-    else:
-        st.error("Default dataset not found. Please upload a dataset.")
-        return pd.DataFrame()
 
-# Main App
-st.set_page_config(page_title="Streamlit App with Static Dataset", layout="wide")
-st.title("Static Dataset App with Upload Feature")
 
-# Sidebar Navigation
-st.sidebar.title("Navigation")
-page = st.sidebar.radio("Go to", ["Home", "Dataset", "Other Pages"])
+st.markdown("""
+    <h1 style="text-align:center; color:orange;">Hotel Data Analysis & Machine Learning</h1>
+""", unsafe_allow_html=True)
+st.markdown(
+    """
+    <img src="https://cdn-uploads.huggingface.co/production/uploads/675fab3a2d0851e23d23cad3/vBi2udNoFPwTnjec40wbw.jpeg" width="100%" />
+    """, 
+    unsafe_allow_html=True
+)
+st.markdown("""
+## Predicting Customer Preferences and Optimizing Pricing:
+##### 📊 Data Exploration and Preprocessing:
+- <span style="font-size:20px;">Cleaning and preparing data by handling missing values, encoding categorical features like *"category"* and *"location,"* and normalizing numerical data such as *"price"* and *"rating."*</span>
+- <span style="font-size:20px;">Analyzing trends in **customer reviews**, **cashback offers**, **discounts**, and **free services** to identify influential factors.
+##### 🤖 Predictive Modeling:
+- <span style="font-size:20px;">**Target Variable**: Predicting key metrics like *price category*, *likelihood of cancellation*, or *hotel ratings.*</span>
+- <span style="font-size:20px;">**Model Selection**: Building ML models such as **Decision Trees**, **Random Forests**, or **Gradient Boosting** for classification or regression tasks.</span>
+- <span style="font-size:20px;">**Feature Engineering**: Extracting insights from **review text** (via text sentiment analysis) or **free services** (binary encoding).</span>
+##### 📈 Model Evaluation:
+- <span style="font-size:20px;">Comparing model performance using metrics like **accuracy**, **F1 score**, or **RMSE**, depending on the task.</span>
+- <span style="font-size:20px;">Employing techniques like **hyperparameter tuning** and **cross-validation** for optimization.</span>
+##### 💼 Insights and Deployment:
+- <span style="font-size:20px;">Unveiling actionable insights from **feature importance** to guide hotel marketing and pricing strategies.</span>
+- <span style="font-size:20px;">Deploying the model in a user-friendly interface to support stakeholders in making real-time decisions.</span>
+##### By integrating **machine learning** with **data analysis**, this project empowers hotel businesses to enhance customer satisfaction, optimize pricing strategies, and maximize profitability.
+""", unsafe_allow_html=True)
 
-# Global state for dataset
-if "dataset" not in st.session_state:
-    st.session_state.dataset = load_default_dataset()
+# # Display an image from a file
+st.subheader("Hotel Data Analysis Model Creation Flow")
+st.markdown("![Beige Neutral Flowchart Graph Template.gif](https://cdn-uploads.huggingface.co/production/uploads/675fab3a2d0851e23d23cad3/owTdXfE7l7CdXQPSaAqBX.gif)")
 
-# Upload a new dataset
-def handle_upload():
-    uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])
-    if uploaded_file is not None:
-        try:
-            data = pd.read_csv(uploaded_file)
-            st.session_state.dataset = data
-            st.success("Dataset uploaded successfully!")
-        except Exception as e:
-            st.error(f"Error reading file: {e}")
 
-if page == "Home":
-    st.header("Welcome to the Static Dataset App")
-    st.write("This app uses a static dataset but also supports uploading a new dataset.")
-    st.write("Navigate to the 'Dataset' page to view or upload a dataset.")
+# Define the URL of the background image (use your own image URL)
+background_image_url = "https://cdn-uploads.huggingface.co/production/uploads/675fab3a2d0851e23d23cad3/FlisTFfpU7flDCWj_KttH.jpeg"
 
-elif page == "Dataset":
-    st.header("Dataset")
-
-    # Dataset Preview
-    st.write("### Dataset Preview")
-    if not st.session_state.dataset.empty:
-        st.dataframe(st.session_state.dataset)
-
-        # Download button for the displayed dataset
-        st.write("### Download the Dataset")
-        csv_data = st.session_state.dataset.to_csv(index=False).encode("utf-8")
-        st.download_button(
-            label="Download Dataset",
-            data=csv_data,
-            file_name="dataset.csv",
-            mime="text/csv",
-        )
-    else:
-        st.write("No dataset available. Please upload a dataset below.")
-
-    # Upload a new dataset
-    st.write("### Upload a New Dataset")
-    handle_upload()
-
-elif page == "Other Pages":
-    st.header("Other Pages")
-    st.write("This section can be customized further based on the app's needs.")
+# 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);  /* Adjust transparency here (0.4 for 40% transparency) */
+            z-index: -1;
+        }}
+        /* Styling the content to ensure text visibility */
+        .stMarkdown {{
+            color: black;  /* White text to ensure visibility */
+            font-size: 30px;  /* Adjust font size for better readability */
+        }}
+    </style>
+    """, 
+    unsafe_allow_html=True
+)