anneadesina/RoomPal-Housing-Shared-Living-PropTech-Data-Analysis-

RoomPal is a data analysis project focused on understanding housing experiences, shared accommodation, roommate dynamics, housing search challenges, fraud, trust, and the use of digital housing platforms in Nigeria. # RoomPal-Housing-Shared-Living-PropTech-Data-Analysis- ## Project Overview RoomPal is a data analysis project focused on understanding housing experiences, shared accommodation, roommate dynamics, housing search challenges, fraud, trust, and the use of digital housing platforms in Nigeria. The analysis uses responses from the Apartment, House-Sharing & Roommate Experience Survey. The objective is to transform raw survey responses into structured, evidence-based insights that can support housing platform development, property management, policy discussions, and user-centered decision-making. The project was conducted entirely in Microsoft Excel, using data cleaning, Pivot Tables, Pivot Charts, filtering, sorting, descriptive analysis, and Excel formulas. Important: This project is descriptive and exploratory. It does not use predictive modelling or advanced statistical modelling. # What Nigerian Housing Data Reveals About Roommates, Rental Stress and Trust in PropTech ## Introduction Finding a place to live should be straightforward: identify a suitable property, assess the cost, confirm that it is legitimate, and move in. For many people, however, the housing search is far more complicated. The process can involve unreliable listings, high costs, limited availability, agents, informal referrals, unfamiliar landlords, potential roommates, and—perhaps most importantly—a lack of trust. This analysis explores these challenges through the **Apartment, House-Sharing & Roommate Experience Survey**, a primary survey designed to understand how people in Nigeria experience renting, shared housing, roommate arrangements, housing searches, and digital housing platforms. Rather than looking at housing purely as a real estate problem, the analysis approaches it as a **user experience and trust problem**. Using **Microsoft Excel**, the dataset was cleaned, segmented, analyzed and visualized through: - Pivot Tables - Pivot Charts - Frequency distributions - Comparative …