Gun Violence in the US from 2013-2016
deborah-digges.github.io
deborah-digges.github.io
Does anyone else find the gun crime in Washington DC strange and/or ironic?
And I assume intentional. This is your work and submission. Exactly what statement are you trying to make? A way to deceive with diagrams?
EDIT: To explain, I haven't looked at the raw data, but reading the diagrams and taking the scale changes into account, there aren't especially big differences year to year, but you're led to believe there are. There could even be an overall nationwide decline for all I know, but the misleading rescaling makes it hard to determine by just looking at the images.
It (the strangeness) is referring to a separate idea in my post, which was the crime level in Washington DC, not the scaling.
I understand why someone would want to use a balanced distribution scale (even though you get weird boundaries sometimes), its so you get the most dynamic visualization and take full advantage of your color library.
What doesn't make sense is redefining the color scales boundaries every time the year changes. As illustrated in this visualization, it intends to lead the viewers to believe violence is getting worse, when in fact the last years maximum number is 5 times lower than the first year.
According to "Homicide in California 2013" (https://oag.ca.gov/sites/all/files/agweb/pdfs/cjsc/publicati...) Table 21, in 2013, there were 1,699 homicide crimes where the type of weapon used was a firearm.
That's just crime data, it doesn't include suicides.
Am I reading this wrong or is the data way off or is it indicating some other kind of firearm violence?
But yeah, still totally off, AFAICT. I also wonder where she got the supposed 2016 data, given that 2016 hasn't happened yet.
Other interesting tidbits from that PDF: almost as many people were killed with ropes, as with rifles. About half as many were killed with knives and blunt objects as were with handguns. Hardly epidemic, if you ask me. Considering how much more convenient it is to kill somebody with a firearm, you wonder why it's not really that much more popular.
the story here is how visualizations are leveraged to manipulate peoples' conclusions. Especially when the conclusions inferred by the data directly contradict the authors' own.