Data Curious 17.07.2017: A roundup of data stories, datasets and visualizations from last week
By: Benjamin Cooley
Tags: Data, Data Visualization, Data Science, Data Journalism, Journalism

Good Reads, Analysis and Tutorials

Scientists from the Proceedings of the National Academy of Sciences published a study on how morally outraged tweeters stay largely within their political social media bubble. Quartz published a summary of their analysis along with their network graph visualization of the results.

News broke of a giant iceberg breaking off the ice shelf of the Antarctic last week. The Guardian produced some brilliant annotated charts to show the progression of the rift. I also found this animated video showing the size of the iceberg quite impactful.

I found this great gif on how summary statistics don’t always tell you much about the big picture. You can read the short blog post write-up about it here.

I discovered a new charting library last week called FactGraphs. It is currently on Kickstarter and is aimed at newsrooms and academic researchers primarily. The interface looks pretty interesting, but not sure how I feel about the design.

BrightTalk is hosting a free webinar on July 19 covering how to use visualization with financial data.

This piece from the Washington Post on solar eclipses in the U.S. has some mind-blowing graphics of spinning globes.

The Pudding produced a visual essay on Dolphins last week. The Free Willy and Flipper by the Numbers analysis is a beautiful example of scrollytelling. Plus, the author introduced a feature I have never seen before: dolphin videos and gifs in column tooltips.

Andy Kirk thinks that when it comes to practicing data viz, you should think like a journalist. I very much agree with him (though I may be a bit biased). His short blog post explains this rationale, but what it really comes down to is curiosity. Working with data is all about asking the right questions.

If you’re getting started using R for analysis and visualizations, this article has some good starter packs to get you going.

Need to scrape some PDFs for data? We’ve all been there. PDFs are the thorn every data person’s side, but luckily there are some handy tools to get around this problem. I like Tabula myself, but this Beginner’s Guide to Extracting Data from PDFs has plenty of other good options too.

Andy Dickinson took a look at this year’s short listed pieces for the Open Data category in the 2016 Data Journalism awards to see how “open” they really were. His Medium post points out that some of these pieces were not entirely open after all. Making data open mean not only means making it available; it also means making it easy and simple to access.

Datasets and other resources

Data.world just released a new feature called Data Projects, which allows you to have a central workspace for multiple datasets and insights about your data. It’s also a really cool way to collaborate with other people interested in data analysis. Read about how you can use it here.

Here are 2 examples of the Data Projects you could get involved in:

If Michael Phelps were to race a shark, who would win? Join this Data Project on data.world to help find out the answer during this year’s Shark Week.

Is there a correlation between UFO & Bigfoot sightings? Analyze the Bigfoot sightings data to find out.

Here’s the dataset that FiveThirtyEight used in their piece Dissecting Trump’s Most Rabid Following. The code and data show how you can trove through comments left on various Trump-related subreddits to start connecting the dots between user personas.

FiveThirtyEight also keeps a Github repo of all the datasets and code behind their data-driven stories. It’s a goldmine.

This blog post from World Bank shows how to effectively use the Health, Nutrition and Population data portal to discover new demographic facts and stats. Good data portal to bookmark if you use lots of world health data.

I found this visualization from Our World in Data on How Much We Think We Spend on Healthcare vs How Much We Actually Do to be fascinating. You can download the data for yourself at the bottom of the chart.

Data visualizations

The Larsen C ice shelf breaking away from Antarctica stole the show for amazing data viz last week.

This one was my favorite: an interactive that places the Larsen C iceberg anywhere on a map to put its size in perspective. It also personalizes the data (try dragging it to your home country and be amazed).

Here’s a helpful D3 bl.ock for showing direction in a dot plot.

This interactive visualization takes a deep dive into the data viz community: a network graph viz of 100 episodes from the podcast Data Stories. Data Stories is hosted by Enrico Bertini and Moritz Stefaner. As you may have guessed, they talk about data viz a lot.

I really liked this infographic on what activities partners do together and apart. The highest and lowest value are predictable (couples eat together frequently, but rarely work together). But some of the bars in the middle reveal a bit more insight.

Have you seen Mona Chalabi’s wonderful hand-drawn data visualizations yet? You should. I love them. They’re simple, effective and memorable, just like all great data visualizations should be.

Speaking of hand-drawn graphs, Peter Yeung from The Times has started doing his own version. But instead of everything being hand-drawn, all his charts involve food of some kind. Keep an eye out for #FOOD4THOUGHT on his Twitter/Instagram feed.

Of course, this week wouldn’t be complete without a Wimbledon visualization. I expect even more to appear this coming week, but for now enjoy this viz showing the dominance of Federer and Cilic (this was before he won the tournament).

Has anyone seen a Depeche Plot before? This viz takes a minute to fully comprehend, but once you learn how to read it I think it’s actually pretty cool.

That’s it from last week. Did you see anything I should have included? Or maybe you just want to give me a digital head-nod/high-five? Tweet me or leave a comment below. I’d also love to see what you’ve been working on lately.