US hate crime trends

[vpenney]

Summary The FBI has hate crime data available for 2004-2016. I'd like to look for trends in both the victims and offenders involved in hate crime, as well as the nature of the crime (robbery, burglary, etc) over the past decade.

As time goes on, it would be interesting to examine these trends in the political climate following the 2016 elections, but that data is not yet available.

Data set(s): https://ucr.fbi.gov/ucr-publications#Hate

Repository: https://github.com/vpenney/data-studio/tree/master/code/02-hate-crime

Possible problems/fears/questions: Joining all of these Excel files might bet pretty tedious.

Inspiration: Stacked bar charts like these should work well. Each bar will represent a year and will measure the types of crimes that comprise the total hate crimes for the year (assault, burglary, etc).

I'd also like to chart the motivational bias (anti-white, anti-Muslim) against the race of the offender.

• [X] I have already spent time with my data set, opening it, exploring it, etc
• [X] I have created a "DIARY.md" file to save links and list all of the terrible, no good problems I come across
• [X] My issue links to my data set(s)
• [X] My issue links to my code repository
• [X] My issue explains what I'd like to explore in the data set
• [ ] My issue includes images - either inspiration or what I've done so far

[vpenney]

I've made one initial graph showing the race of people who commit hate crimes against other people (as opposed to property), but still have a lot of data to clean, merge, and graph.

Problems/Questions

Right now, I'm still thinking through how best to visualize my data.

Checklist

• [X ] I have included my visuals
• [X ] I have filled out the sections above
• [X ] I have been updating my DIARY.md with details about my process
• [X ] I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository

[playfairbot]

Howdy! I'm a little robot, let's take a peek.

You need some feedback, let me summon @benbitoun, @mattrehbein, @linleysanders for you

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[mattrehbein]

I really like the story idea and the angles you propose. The chart you have so far is a little hard to read; if that one will just show the numbers of hate-crime offenders by race, maybe a simple bar chart would be easier to understand?

I'm most interested in the 'who-were-targeted' numbers, so I will look for when you post how that looks in graph form!

Nice work so far!

[linleysanders]

• I'm a little confused why there are such dramatic dips in the line chart—maybe if this was done in a bar chart with the type of crime listed on the x-axis, it would be more intuitive.
• I think a subhead indicating that "white people were most likely to commit hate crimes between 2004-2016."

[vpenney]

Update

This first graph is total hate crimes in the US in 2016, broken down by the motivation for the hate crime (race, religion, disability, etc) and the race of the offender:

I feel like there's a lot of press for race and religion-motivated hate crimes, so I filtered those crimes out and got this:

It's an interesting graph, and suggests that a far higher percentage of the total hate crimes committed by non-whites are motivated by things other than race and religion. The issue I have with it is that out of context, it's misleading, because it appears that white and black people commit the same number of hate crimes.

I went one level deeper to look at gender and gender-identity motivated crimes, and found that apparently, only white people commit "anti-male" crimes. Of course, there are lots of hate crimes committed against men, but seemingly only white people have a primary motivating factor of "I dislike you because you are a man."

Any changes in direction or topic?

No real changes in direction--the main struggle has been finding a focus instead of just regurgitating data.

Problems/Questions

• I'm wary of the lack of total hate crime data in my more granular charts, because it appears that different groups are committing the same number of hate crimes, when really they're committing similar numbers of certain types of hate crimes. Is there a better way to visualize this than bar charts? Maybe a gridplot?

• I still have a few more spreadsheets to go through, but I may be able to find the gender of hate crime offenders and look at the types of crimes that men vs women commit, which hopefully people find interesting? I dunno.

• I'm working on finding a way to see if women or men committed hate crimes that were motivated by anti-male sentiment, as well as the type of crime. These crimes aren't all violent crimes--some are vandalism or theft. More on this later.

Checklist

• [X] I have included my visuals
• [X] I have filled out the sections above
• [ ] I have been updating my DIARY.md with details about my process
• [X] I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository

[troboukis]

I'd make the second graph of hate crimes (the one where you filtered out relegion and race, as a 100% stacked bar. The same with the following maybe.

[vpenney]

Final

Project visuals/text

Here are my visuals:

For text, check out my webpage, where it's all laid out nicely and hopefully makes sense

Details

Headline: How does the U.S. hate?

Published website version: You can find it here.

Code repository: Code is here.

Final data set(s): Data is here.

What did you find to be the most difficult part of this project?

I was working from government data, so I had a plethora of nearly-identical Excel documents to hunt through, clean up, and merge. Instead of having too little data, I had too much, which made it difficult to find and focus on one narrative.

Are you satisfied with what you produced? Is there anything you would like to change or improve?

Overall, I'm satisfied with what I produced, although I'm getting a little tired of bar charts. I may make a waffle chart for this project later, just for fun.

Checklist

• [X] I have included my visuals
• [X] I have posted my project to my project website
• [ ] I have been updating my DIARY.md with details about my process
• [X] I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository

[malbasi]

The final product came out great and there is some very interesting information in the data. There are still a few things that are a little 'off' for me though. First, the color scheme is very bright and fun. It doesn't quite fit with the subject matter. Maybe next time use the same colors, but more muted tones for such dour data. Second, you crammed a lot of info into the last chart. So much that I feel like it lost its impact. I think you could have skipped the motive category and just left it as a total. Really, the point of the chart is to show the 'where' not the 'why.' Your earlier graphs showed the 'why' well, no need to bring it back in the final.

Great job!

[Palarisk]

This is such a great job! If you'd continue working on this, I'd love to see this adjusted to the size of the white/black/etc population.