Data Analysis: Building Evaluations in Toronto

An analysis into how buildings are scored to keep renters safe in the City of Toronto.

Dataset

• City of Toronto Open Dataset
• Evaluation scores for buildings registered with RentSafeTO.

What is a building evaluation score?

A metric determined by property investigators for how well a building complies with bylaws. Investigators factor in several categories + achieve violations to determine the score. For more information, see here.

What sort of buildings are we looking at?

The majority (84.2%) of buildings being evaluated are private.

Is there a discrepancy between Private vs Social Housing and Toronto Community Housing?

According to the building evaluation reports … not really. The average statistic for each building evaluation by property type is roughly the same.

Private — Mean = 87.23. Median = 89.

However, compared to Social Housing and TCHC, Private apartments have many more outliers. Under private housing, a lot more apartments have far below-average scores, which may indicate that there are different guidelines for apartments owned by a private company/individual or a municipal body.

Social Housing — Mean = 89.44. Median = 91.

TCHC — Mean = 86.54. Median = 87.

Where are these buildings located?

According to this heat map, the buildings in Scarborough (88+ evaluations) are the most up-to-date with building bylaws established in Toronto. These buildings have the highest evaluations, closest to 100, which would be a perfect score. I used the median instead of the mean to represent the scores to account for outliers.

The buildings in Humber River-Black Creek (83), Davenport (82), and Beaches-East York (83) are worse and not up to code as well as the buildings in Scarborough.

Limitations

• RentSafeTO excludes condo buildings, townhouses, and units in private homes, like basement or main floor apartments. I think we would see the evaluations to be slightly lower, especially in homes converted to apartments. However, it’s very possible that condos would bring those averages up, especially in the core downtown.

Conclusion

This is a quick analysis. I think it’s cool to see in the form of a map how building evaluations vary throughout the city and make those comparisons. Other than that, I found that there were limitations to this dataset regarding the actual analysis. It’s more like a spreadsheet that provides insight into the actual evaluations.