It's always really important to understand what you're analyzing when dealing with crime data. In this case this is when crimes are reported or when arrests are

It's always really important to understand what you're analyzing when dealing with crime data. In this case this is when crimes are reported or when arrests are made. That's not the same thing as when the crime occurs. So the spikes for burglary in the morning and at lunch hour are more likely because that's when people notice the crime has occurred and call the cops, not when someone is actually breaking in. And the prostitution trends are probably when the cops are choosing to be out and about arresting, which might not at all be correlated with when the most illegal activity is actually happening. It's interesting that the author thinks the spikes on the first of the month are bad data, but that the huge spike in sexual assault on Jan 1 of each year is valid data. I wouldn't doubt that there are slightly more sexual assaults on new year's eve, but on the order of 10x more than any other day of the year? That doesn't seem right. I'd guess there are more nuances about how sexual assaults are reported or logged that are at play here.