Source: ARMLS, 1/9/2024
I used Python to analyze and visualize real estate sales data for Maricopa County, focusing on the performance of different zip codes in the year 2023.
Key Steps and Features:
- Data Loading and Preparation:
- The script starts by importing the necessary Python libraries for data manipulation and visualization.
- It then loads a CSV file named ‘2023_final_modified.csv’, which contains real estate sales data.
- The script ensures that the ‘COE’ (Close of Escrow) dates in the data are correctly formatted for further analysis.
- Data Filtering:
- The script filters the data to focus only on sales that occurred between January 1, 2023, and December 31, 2023.
- Data Aggregation:
- It groups the filtered data by ‘ZipCode’ and counts the number of sales in each zip code. This step is crucial to identify which areas are more active in terms of sales.
- Identifying Top Performing Zip Codes:
- The script sorts and selects the top 10 zip codes based on the highest number of sales. This highlights the most popular areas for real estate transactions during the year.
- Visualization:
- The data is then visualized using a bar chart, making it easy to compare the sales performance across different zip codes.
- Each bar in the chart represents a zip code and is color-coded for clear differentiation.
- The chart includes labels and annotations, such as the number of sales per zip code and the source of the data for credibility and reference.
Utility for Real Estate Agents and Loan Officers:
- This script is a valuable tool for real estate agents and loan officers as it provides a clear and immediate visual representation of market trends and hotspots within Maricopa County.
- By understanding which areas are seeing more sales, professionals can better target their marketing strategies, identify potential areas for investment, and advise clients effectively based on data-driven insights.