This project uses time series analysis and forecasting techniques to explore crime data during the COVID-19 pandemic, while also considering the weather.
Did COVID-19 prevent homicides?
Admittedly, that header is a bit sensational, but when I analyzed Boston’s crime data during Covid-19, the drop in reported offenses was quite astonishing. While verbal dispute offenses sky-rocketed, and more people set out to rob a bank, the overall number of crimes dropped by more than half. So indeed, the lock-down prevented harm by reducing the risk of catching the virus and also decreased the probability of getting hit by a car or bullet.
Continue reading “(Don’t) Blame the weather”
I feel rueful. I’ve learned Tableau. A proprietary tool [cue the horror-movie sound].
Nothing wrong with that, you say? Well, I felt like a traitor, given that my book, Computing Skills for Biologists, spends many pages on why to prefer open-source software over proprietary tools.
In academia, some people carry it like a badge of honor that they don’t have Microsoft Office installed. While the intentions are good (accessibility of open source tools for everyone), the choice turns out less clear cut in an industry setting.
Continue reading “Tableau vs R”
I am writing this at a time when COVID-19 paralyzes the world. The fatalities, geographic patterns, and economic impact of the disease are subject to fantastic visualizations elsewhere.
However, the lockdown in response to the disease has an impact on almost all aspects of our life and, hence, creates striking patterns in otherwise consistent data.
Here, we’ll take a look at other (equally sad) graphs—the crime statistics in Boston. Did the number of reported offenses change during COVID-19? Did the occurrence of specific offenses vary in comparison to other periods?
Continue reading “Boston crime in times of COVID-19”