Jacembenhlima/Tunisian-Real-Estate-Market-Analysis-using-Power-BI

# Tunisian Real Estate Market Analysis using Power BI ### Project Link : drive.google.com ## The idea This project explores property prices in Tunisia using a dataset that includes property categories, sizes, prices, and location details. The goal was to uncover trends, relationships, and key insights in the Tunisian real estate market by using advanced data analysis and visualization techniques in Power BI. The analysis focuses on understanding the price distribution across different property types, comparing prices in various cities and regions, and examining how property size impacts price. ### Key Questions Explored - What are the average property prices for different categories (e.g., apartments, land)? - Which cities and regions have the highest and lowest average property prices? - How do prices differ between properties for sale and for rent? - What is the relationship between property size and price? - How does the number of rooms and bathrooms impact the price? - What is the price distribution across properties in different regions? ### The process - Step 1 : Loading the Dataset Data Loading and Initial Exploration: - The dataset was loaded into Power BI, containing various attributes like city, price, region, category (e.g., apartments, land), and whether the property was for sale or rent. - I first explored the dataset by checking the distribution of property types (For Sale vs. For Rent) and ensured that the columns were clean and ready for visualization. - Step 2 : Cleaning the Data - Step 3 : Bar Chart: Count of Property Prices by Category Objective: To understand the distribution of properties by their category (e.g., apartments, houses, land). Visualization: A bar chart was created showing the count of properties by category. This provided an overview of the most common property types in the dataset. - Step 4 : Map Visualization: Property Prices by City Objective: To vis …