MarwanEhab1/Egypt_Houses_Price_Project

Real Estate Sales Analysis Project Analyze and predict property prices in Egypt using data cleaning, exploratory analysis, feature engineering, and machine learning models. Provides insights on property distribution, price ranges, and predictive analytics for informed decision-making. # Egypt_Houses_Price_Project # Egyptian Real Estate Price Prediction: A Regression Analysis ## Overview This project focuses on developing a robust Machine Learning model to **predict the sale price of real estate properties** (Apartments, Villas, Chalets, etc.) across various cities in Egypt. By leveraging key attributes such as size, location, type, and finishing status, we aim to provide an accurate predictor for potential buyers and sellers in the dynamic Egyptian housing market. --- ## Project Pipeline The analysis followed a comprehensive data science methodology: 1. **Data Acquisition & Cleaning:** Initial data inspection, handling of missing values (replacing 'Unknown' with $\text{NaN}$), and removal of duplicates. 2. **Data Preprocessing & Feature Engineering:** * Standardizing categorical values (e.g., unifying 'Standalone Villa' types). * **Advanced Feature Handling:** Logically inferring and mapping property **'Level'** (Floor) based on **'Type'** (e.g., Penthouses are 'Highest', Villas are 'Ground'). * Converting categorical features (Type, City, Delivery Term) into numerical formats using **One-Hot Encoding**. 3. **Outlier Treatment:** Applied the **Interquartile Range (IQR)** method specifically tailored for price analysis **per city** to ensure removal of unrealistic prices based on local market norms. 4. **Exploratory Data Analysis (EDA):** Visualizing price distribution, feature correlation, and key market trends. 5. **Model Training & Evaluation:** Training five different regression models and comparing performance metrics ($\text{R}^2$, $\text{MAE}$). --- ## Key Features The models were trained on the following property attributes: | Feature | Data Type | Description | | :--- | :--- | :--- | | **Area** | Numerical | Property size in square meters. | | **Bedrooms** | Numerical | Number of bedrooms. | | **Bathrooms** | Numerical | Number of bathrooms. | | **City** | Categorical | The property's geographical location. | | **Type** …