It was hotter in 2015 than any other year ever. K. K. Rebecca Lai for the New York Times shows just how much hotter it was in your city. Simply type in your city name or click on the arrows to browse to see a time series for the year.
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Plants and animals interact with each other to stay alive, which in turn forms complex systems. I think the Lion King covers the system simplistically in song-form at the beginning of the movie, but that doesn’t cut it when trying to predict the effects of things like climate. Jianxi Gao, Baruch Barzel, and Albert-László Barabási study the complexities of nature’s network in greater detail.

Mauro Martino helps explain the work in this video for Nature. [Thanks, Mauro]

Last month, I published an interactive visualization that simulates how and when you will die. It reached millions of people worldwide, and I basically had one eye glued to the real-time traffic dashboard for a week. It was kind of nuts.

A few days in, I woke up and checked the stats. The Daily Mail was in the referral list. I clicked through to the article and my interactive was fully embedded on the page, which was strange because I didn’t give permission to do that.
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The Upshot has been doing a good bit on the Supreme Court dynamics after the death of Justice Antonin Scalia. In their latest, Alicia Parlapiano and Margo Sanger-Katz look at major shifts over the decades from more conservative to more liberal and vice versa.

The shifts are based on Martin-Quinn scores, which take past court decisions into account. You can grab the data here.

Noah Lorang, a data scientist at Basecamp, explains the key for most companies isn’t finding a way to use the most advanced methods. Instead, it’s about asking the right questions.

The dirty little secret of the ongoing “data science” boom is that most of what people talk about as being data science isn’t what businesses actually need. Businesses need accurate and actionable information to help them make decisions about how they spend their time and resources. There is a very small subset of business problems that are best solved by machine learning; most of them just need good data and an understanding of what it means that is best gained using simple methods.

Much along the same lines as when I say you can think like a statistician without the math.

For my graphic on emergency room visits over time and the other on things that get stuck, I used data from the National Electronic Injury Surveillance System, which is maintained by the Consumer Product Safety Commission.

You can download the data, grouped annually, as Excel files and then do some munging to get the data in order. It’s not a huge burden, but it’s not that fun either. Or, if you want to skip straight to the good stuff, you can use the neiss R package by Hadley Wickham to import the data in R.

I’d go with the latter.

Numberphile, from the Mathematical Sciences Research Institute, is one my new favorite YouTube channels. In this episode, Hannah Fry talks crime, data, and the Poisson distribution.

[Thanks, Mike]

Crime and data have an old history together, but because there are new methods of collection and analysis these days, there are new decisions to make. The Marshall Project, in collaboration with the Verge, looks at the current state of predictive policing and the social issues that surround it.

As predictive policing has spread, researchers and police officers have begun exploring how it might contribute to a version of policing that downplays patrolling — as well as stopping, questioning, and frisking — and focuses more on root causes of particular crimes. Rutgers University researchers specializing in “risk terrain modeling” have been using analysis similar to HunchLab to work with police on “intervention strategies.” In one Northeast city, they have enlisted city officials to board up vacant properties linked to higher rates of violent crime, and to advertise after-school programming to kids who tend to gather near bodegas in high-risk areas.

Of course, then there’s the whole action-reaction stuff. More time required.

People with certain professions tend to marry others with a given profession. Adam Pearce and Dorothy Gambrell for Bloomberg Business were curious.

When it comes to falling in love, it’s not just fate that brings people together—sometimes it’s their jobs. We scanned data from the U.S. Census Bureau’s 2014 American Community Survey—which covers 3.5 million households—to find out how people are pairing up.

You get a matrix of professions organized by more male to more female, left to right. Mouse over any profession or use the search box and lines project out to the five most common professions that the one of focus tends to marry to. The pink and blue color gradients indicate the sexes of the two spouses.

So for each profession, you get a quick view of who people marry, whether it be outside their own or within. I like how when you mouse over the far left or the far right, you see lines jut across to the opposite side. I wonder what the tendencies are in total for male-dominant to marry female-dominant professions and vice versa.

China’s economic slowdown means a major decline in imports from other countries, which leads to significant effects in these areas. The Guardian takes a look. The vertical axis represents lost export income as a percentage of GDP, the size of the outer red circle represents GDP, and the inner white circle represents exports to China. Dollar units are in billions of dollars. Billions.

Data can be intimidating and confusing for beginners, and as a result they stay away from the spreadsheets and delimited files altogether. DataBasic, a suite of tools built as an introduction to poking at data, injects a bit of fun into the onboarding process.
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A fun one from Interactive Things that shows cover songs with a galaxy metaphor:

The panorama view shows the 50 top songs as individual planetary systems with the original work as the sun. Each planet represents a version of the song and it’s appearance indicates characteristics including genre, popularity, tempo, valence, energy, and speechiness. The radius of its orbit around the sun shows the years between the publication dates. This view allows you to compare the structure and density of the constellation of different songs from a high-level perspective.

A high percentage of Americans are glued to the television or party sample platter during the Super Bowl each year, which is especially obvious if you go anywhere without a television during this time. Todd Schneider for the Upshot looks at this phenomenon through the lens of New York taxi rides per minute.

Taxi activity’s lowest level in New York coincided with the climactic moment of the game, just as Malcolm Butler intercepted Russell Wilson at 9:59 p.m. to secure the 28-24 victory for the Patriots. New England called a timeout after Butler’s interception, but many Super Bowl party guests apparently didn’t wait around to watch Tom Brady take a knee before they hailed cabs.

Fun. Although nothing beats the Canadian toilet flushing symphony during the Olympic gold medal hockey game of 2010. [Thanks, Todd]

As we use up current energy resources, it grows more important to look to alternative energy sources. Wind is one potential area, but the problem is that one has to know where it’s windy enough — now and in the future — to justify the cost of building the structures to harness the energy. It’s freakin’ wind, and variability is all over the place.

Project Ukko is an effort to make wind research predictions accessible to those who need such information. The visualization component by Moritz Stefaner, in collaboration with Future Everything and BSC, shows a number of wind factors around the world.
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Back in 2008, the New York Times rolled out a campaign finance API so that you could easily access data based on Federal Election Commission filings. (If you’ve tried grabbing data direct from the source, you know this is a pain.) ProPublica took the reins a few days ago as we lead up to this year’s elections.

Like millions around the world, you’re probably like, “What the what? I thought the FEC released their own API recently!” They did. But:

One big difference is timeliness: the FEC API is updated nightly, while ours will be updated throughout each day. For many users of campaign finance data, that distinction may not be a big deal, but on filing days, when thousands of filings are submitted to the FEC, timeliness can matter a lot. Another is the source data: the FEC considers electronic filings to be “unofficial” in the sense that data from them is then brought into agency databases before being published as bulk data. The FEC API publishes data only from those official tables, while the ProPublica API has data from both the official tables and the raw electronic filings.

I’d trust the ProPublica one more for now.

There’s a lot of data on criminal justice — prison populations, crime rates, police policies, etc — but it can be hard to find, because it’s scattered across and deep within thousands of local sites. Hall of Justice from the Sunlight Foundations is an effort to catalog a significant portion of reports and datasets.

While not comprehensive, Hall of Justice contains nearly 10,000 datasets and research documents from all 50 states, the District of Columbia, U.S. territories and the federal government. The data was collected between September 2014 and October 2015. We have tagged datasets so that users can search across the inventory for broad topics, ranging from death in custody to domestic violence to prison population. The inventory incorporates government as well as academic data.

Dealing with those pesky government PDF files is up to you. At least there’s an app for that.