The real estate transactions dataset was published by the Dubai Land Department on Dubai Pulse government website which is an open-source data repository. I then uploaded it to Kaggle for analysis using Kaggle notebooks.
The purpose of this analysis is to explore the real estate transactions identifying trends and patterns and to get a better understanding of the dataset using Python on Jupyter notebook.
1. What are the areas with the highest and lowest average price for residential properties?
2. How have number of property transactions changed over time?
3. How have residential property prices changed over time?
3.1 Are there any seasonal patterns in property prices?
4. What is the proportion of Residential properties in 2023?
4.1 What are the proportions of different types of residential properties?
Exploratory data analysis on Real Estate Transactions using Python with Jupyter notebook on Visual Studio Code then imported to Kaggle notebooks for sharing.
Click here to see the full analysis on Kaggle.
Click here to view an interactive version of the result.
1. What are the areas with the highest and lowest average price for residential properties?
2. How have number of property transactions changed over time?
3. How have residential property prices changed over time?
3.1 Are there any seasonal patterns in property prices?
4. What is the proportion of Residential properties in 2023?
4.1 What are the proportions of different types of residential properties?
• The area with the highest median price of residential properties is Island 2, while Al Lusaily has the lowest median price.
• The number of transactions were constant until 2007 with sudden increase in the year 2008 and 2020.
• Yearly median price of residential properties showed a significant increase starting from 2001.
• A trend in monthly median price of residential properties showed that the highest median price is in the middle of the year.
• Residential properties accounts for 92.1% of the total transactions in 2023.
• Unit-type properties for residential use accounts for 83% of the total transactions in 2023.