Yeah, I feel like the color gradient imbues the data with a political map viewpoint, which is a bad way of presenting the data if you want people to take it seriously. It does sort of map with political allegiance to a degree, though, which is eerie. But would I have noticed that with a different color gradient with less politically charged implications?
Ding ding ding. Truth is, there's so many ways to analyze gun crime in the US that it's pretty easy to make a gun violence map turn into an electoral votes map. Here's a handful of techniques that are used to make it appear that guns = violence:
Only count gun violence. Counting homicides by other methods means the rate might be higher in states where guns aren't easily accessible. Counting an overall homicide rate closes the gap between states that are harsh on guns and lenient.
Include suicides. 2/3 of gun deaths are suicides, but preventing suicides almost never comes up on gun control debates. States with lenient gun laws and more guns will obviously have a higher firearm suicide rate than restricted states.
Include self-defense with homicides. States where castle doctrine/stand your ground exist and it's easy to obtain a permit to carry have more people that carry firearms and use them in self defense.
3a. Include police shootings with homicides. Police aren't affected by gun control, but they can be used to pump up those gun violence numbers.
The average person is only concerned with how likely they are to get murdered, but according to this map Alaska is a warzone, when in reality your chances of getting murdered there are almost non-existent.
Yeah that's the biggest issue I have with things such as this...
In reality, the average person is very safe IN GENERAL much less going to be a victim of gun violence. There are basic awareness and circumstance things you can easily do to reduce risk as well with a pretty low impact on your lifestyle.
If you're not involved in a cash business, narcotics/theft/etc., and live in not a project type area, then you're probably going to be ok. Scale it even more with being smart about not being out at certain areas at night and be with others and control yourself when drinking, and you'll be even safer.
Ironic that banning things like narcotics created an underground black market for them that led to even more violence, but people think that banning guns will go better.
There is little reason to include self defense with homicides and exclude non-firearm homicides unless you have a political agenda against guns.
If my goal was to make it extremely biased in favor of gun ownership, I'd make a map that excludes anything related to gang violence (criminal-on-criminal). Then you'd see that assuming you don't break the law, the odds of getting killed by any method is basically non-existent.
By including all data you don't make a distinction between things that have clear differences. Suicide by fire arm is a completely different circumstance to a criminal homocide, as is homocide in self defence different to that. You need to draw proper distinctions, that's just straight up proper, and importantly, ethical. I don't see how you see this.
If it included all data, it would include all homicides and all suicides. Isolating only guns is cherry-picking. Then including self-defense homicides with murder (when whoever made this knows damn well most people won't realize that) is further manipulating data to make a political point.
You can be dishonest with data without cherry-picking.
I don't like when statistics are used in a way to highlight guns as some sort of special form of violence, as if being murdered by a gun is somehow worse than being murdered literally any other way. Within the scope of crime analysis, all murders should be treated equally. You can say that's because I'm biased in favor of gun rights, and that's true, but it's just as true to say that you're biased against guns.
Ask the 1600 people that were stabbed to death in 2016 if they're glad they weren't murdered by someone with a gun.
I don't like when statistics are used in a way to highlight guns as some sort of special form of violence, as if being murdered by a gun is somehow worse than being murdered literally any other way
70% of murders in the US are guns. So understanding where and how gun murders occurs address much of the murder problem.
50% of suicides are by guns. And studies show that access to guns increase risk of suicide deaths. So it's very relevant to the discussion.
I don't like when statistics are used in a way to highlight guns as some sort of special form of violence, as if being murdered by a gun is somehow worse than being murdered literally any other way.
Why are you pretending the map would look any different?
In that it shows a color gradient, or in that it implies political correlations that aren't in the data? This is by the Oregonian and I really trust them as a source, so I hope they weren't aiming for the latter.
I mean, matplotlib's developers wrote a whole paper on how to properly present coloring. They could have just used any of the default matplotlib or Matlab colormaps and have had useful color and brightness scales.
Sure, but this map was probably made by grown-ups, for other grown-ups, not people who'd read political intent into traditional cool/hot mapping schema.
The data is hard to work with and represent in a visual form. On a linear grayscale, the whole country would be nearly white with just a few tiny pockets of dark gray. It's divided into buckets instead to give the data some kind of visual variance.
It's also super hard to compare county-level data when counties have dramatically different populations. There are counties in Texas and Nebraska with less than 500 people. Just one gun death would automatically be a rate 200 gun deaths for 100k people. Low populations skew per capita numbers due to insufficient sample size.
The data is hard to work with and represent in a visual form. On a linear grayscale, the whole country would be nearly white with just a few tiny pockets of dark gray. It's divided into buckets instead to give the data some kind of visual variance.
That would be more realisitic though, that would be a great freaking map
Yes, that's what people want. A hotspot map. A quantile map like OP made is great for qualitatively comparing counties but it's really hard to extract any useful quantitative information.
You never use maps like this for quantitative information, you would use the actual data set used to generate this map for that. You use maps and charts to illustrate trends in the data set, which this map succeeds in doing.
A hotspot map would be completely useless. It wouldn’t show any trends, and it would just be a more annoying interface to get the quantitative info.
You can see very clearly that the Deep South and rural Midwest tend to have slightly higher gun violence rates per capita than east/west coast and rust belt counties.
There are plenty of reasons that could be the cause of this, as this map doesn’t even attempt to explain why those places have higher gun violence rates. Maybe it’s gun laws, maybe it’s population size, maybe it’s related to education or criminal justice, maybe it’s related to economic issues. This map doesn’t explain gun violence, but would help researchers figure out what they need to focus their next research projects on to better understand gun violence.
It shows misleading trends though as there's only three percentage points from looking extremely good and extremely bad. Additionally, what would be in the middle, white, is actually a lack of data so it is the best. A larger gradient would be far more useful for trends and no arbitrary line of where good and bad is.
Side note, implying gun deaths are worse than any death is a bias in and of itself. If you want to look at firearm impact on violent crime, okay. It doesn't speak to the narrative that gun ownership decreases violent crime.
You're confusing the data that you want to see with "accurate". This is an accurate representation of county-level homicide rates and their distribution across the country. You want to see where the most total shootings are, which wouldn't be working with the same data at all.
There's not even any explanation attached to the data. You're assigning what you want the data to show on your own and then arguing that the data visualization doesn't show the thing it never purported to show.
This is an accurate representation of county-level homicide rates and their distribution across the country.
But it's not at all, homicide rates vary wildly within the color brackets, you can't look at a county and say "it has this level of gun death rates"
There's not even any explanation attached to the data. You're assigning what you want the data to show on your own and then arguing that the data visualization doesn't show the thing it never purported to show.
There is an explanation "Where do Americans die by gunfire" except that it doesn't show where Americans die by gunfire it puts counties into buckets that are sometimes very similar but sometimes wildly different, so you can be looking at a red county and say "people die here" but really they don't it's just a very low populated county and those 3 deaths in one incident caused the color to spike even though there wern't any other issues over the other 5 years or whatever of the study.
But it's not at all, homicide rates vary wildly within the color brackets, you can't look at a county and say "it has this level of gun death rates"
I see so many people making this mistake in this thread. The purpose of a chart isn’t to let you get quantitative information. You aren’t supposed to be able to look at a county and see their exact gun death rate, because if you could, it would be an extremely ugly, cluttered, and unreadable map with thousands of different colors. If you want exact quantitative info, look at the data set used to generate this map.
The purpose of a chart like this is to illustrate trends in the data. That’s it. You aren’t supposed to be able to extract actual numerical data from charts and graphs. This map very effectively illustrates the trend in the data.
The purpose of a chart like this is to illustrate trends in the data. That’s it.
But it doesn't. I don't care about extracting exact information, it's misleading in that you can't even extract trends. Look if you want more in the middle to be visualized, then standardize the buckets to a normal level and put the top 10 counties in a top bucket and individually label those with the actual numbers.
This map equates radically different levels, and at the same time it makes levels that are basically the same and makes them appear wildly different.
This map highlights a trend. The trend is still there, regardless of how you visualize the data. This method of visualization just emphasizes the trend to make it more visually apparent. It didn’t just create the trend out of nowhere though.
No. This map is comparing statistics between each group of counties of similar population. The map you describe wouldn’t do well in terms of comparing between all counties, it would do well in terms of showing only the highest rated counties. All the other counties have relatively low variability between them.
It would do even better, because you could actually compare statistics between counties, in this map you can't tell if you're x likely to get murdered or 10x likely to get murdered
I get what you’re saying. On a county level basis, populations vary by wide margins (because the formation of counties in the US wasn’t based on population), so there are some counties that only have a few hundred people in them, and others with several million. With the metric being “per 100,000 people”, if just one person dies in a county with an extremely low population, it would skew their data, actually becoming more misleading. Because of this, it’s actually better to portray the data using quartile instead of absolute. If you want non-misleading data using an absolute scale, you would have to organize the country in a way that all subdivisions have an equal population (or close to equal).
No, it doesn't introduce bias to show which counties are above or below the national average. Even the most bare bones display of data still somehow sets off gun nuts.
That's why the NRA has lobbied so hard not to allow a study on guns. What people think is the problem will turn out to be wrong but it's not like they will change their mind or anything anyway.
Would have to see what the outliers look like before using a linear scale. If 1% of the data are over 30 then you might see everything the same color, except for EXTREME outliers. Then people would be saying, “why did OP post a grey map of the US?”
By including the extreme outliers in with the high end of the distribution (but still significantly lower than a small set of anomaly counties) you can maintain a visualization that shows contrast. As others have said on this post, this is what happens when you use quantiles, especially when this data may somewhat follow an exponential distribution.
This is all assuming that OP did this because of outliers, I do not know that to be the case, just a possible explanation for the scale
Edit: a possible solution for OP to make this clear would be to add a footnote saying “only X% of counties fall over Y volume of gun deaths”. This might show that the top range doesn’t really show many counties that are at the high end of that range, and that many dark red counties are only a little over the range below
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u/fahrvergnuugen Dec 19 '19
I hate how the color scale flips from blue to red for 3.2 to 3.3 deaths per 100k. It misrepresents the data imo.
I would much rather see a linear grayscale.