Inspiration : With the growing enrollment at the University of Cincinnati, international students are increasingly focused on off-campus housing near the university. Our primary concern is the trend in rent prices in the CUF area, which directly impacts our cost of living in the U.S.
What it does : This data visualization project analyzes three key aspects of the housing market: pricing, demographics, and market trends. Using Census data from CUF, we explore historical trends in house prices and rents, demographic shifts, and forecast future changes. Our analysis also highlights the availability of university housing and the increasing demand from students.
How we built it : We utilized Census data from 2010 and 2020 on CUF housing. After cleaning and refining the data, we generated insights and developed visualizations to best represent these findings. We categorized the data into relevant charts and graphs to effectively illustrate our perspectives.
Challenges we ran into : One of the biggest challenges we encountered was cleaning and organizing the data. Due to the vast amount of data available on this topic, we had to carefully filter and format it for consistency and clarity before analysis. It took considerable time and effort to ensure the data was accurate and relevant.
Accomplishments that we're proud of : We are proud to have completed the project with all the data visualizations we envisioned. The process taught us valuable skills in data extraction, cleaning, and transformation, allowing us to effectively model complex datasets.
What we learned : Through this project, we gained valuable experience in several key areas. We engaged in comprehensive data exploration, uncovering trends and patterns that informed our analysis of the CUF neighborhood's housing landscape. Using Power BI, we developed data visualizations that effectively communicated our findings, enhancing our ability to tell a compelling data story. Along the way, we tackled and resolved data bugs, sharpening our problem-solving and analysis skills. Additionally, this project fostered strong teamwork as we collaborated to refine our insights and deliver a cohesive presentation. Ultimately, we honed our presentation skills and developed our ability to translate complex data into actionable insights through effective data storytelling.
What's next for Cincinnati CUF Housing Analysis : Is there a rise in long-term renovations or property flips that are not immediately re-entering the rental market? The increase in "other vacant" units might reflect properties undergoing extensive renovations or being held for future resale rather than being rented out. Investors could be targeting CUF for property flipping or redevelopment, temporarily taking units off the rental market, which could explain the corresponding drop in "for rent" properties. Could the COVID-19 pandemic have contributed to temporary or strategic vacancies? The COVID-19 pandemic has severely impacted the economy, creating financial constraints and legal matters related to pledging assets for landlords that have prevented them from renting out their properties. As a result, there has been an increase in properties classified as "Other Vacant" and a decrease in those listed as "For Rent." Are properties being removed from the rental market due to disrepair or regulatory issues? A significant portion of the decrease in "for rent" units could be due to properties falling into disrepair, becoming uninhabitable, or not meeting city codes, resulting in these properties being reclassified under the "other vacant" category. This could indicate maintenance or investment challenges among property owners, particularly in older housing stock.
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