How does trash impact the ocean? This infographic paints a pretty picture on an ugly topic. It’s not easy to make a swirl of trash in the mid Pacific look interesting, but this infographic pulls it off swimmingly. The entire infographic is a loose federation of different topics: how trash gets to the ocean, the type of trash, effected animals, and the impact on food chain.
Most infographics would focus too much on walking the reader through each bit, but the organization lets the reader explore the topic without an annoying, forced flow. It is also a pleasant combination of dashboard-style numbers, minimalist bar charts, map, and illustrations. Using bubble plots is always dicey, but works nicely in this circumstance since it’s used sparingly.
I couldn’t find a higher resolution image, a drawback at this point. This infographic has a low data-to-ink ratio, but I think the spacing and illustration restraint is evident here.
Two things can be said about Nobel prize winners with almost complete certainty: they’re old and are at top-tier universities. So I thought, but my knowledge of Nobel prizes are heavily weighted to economics and the physical sciences. An infographic by Giorgia Lupi, Federica Fragapane, and Francesco Majino helped me realized I was wrong.
Recipients in physics were comparatively young at the prize’s inception. While most recipients in the sciences, medicine, and economics came from Ph.D. granting universities—mostly from a select few colleges—Peace and Literature prizes were awarded to non-academics.
It’s infograph is far from perfect, however. The infographic comes with instructions on how to read the it—a bad omen for data visualizations. But the infographic can still be understood, and with some patience, highly appreciable.
Hey, if you don’t recall, we’re not in a recession. HOOORAY! Bad news though, it’s a slow recovery. For months econ. blogs have posted graph after graph showing the slowness of the recovery. Now, to be fair, economists complain about the slowness of an economic recovery the same way each presidential election is the dirtiest ever seen. Nevertheless, John Schwabish has create a great, straightforward infographic showing the current recovery is the slowest.
The infographic presents three pieces of important data: historical gains/losses of GDP; quickness of a recovery after a recession; and the significance of past and current recoveries. None of this is groundbreaking, but it’s worth mentioning since it’s presented in one whereas others have divided these
A feature I love for any graph are data pointers. Here, John uses subtle indications for average growth/decline and markers for recessions. Any reader can easily spot fluctuations of GDP, the depth of the recent recession and that the 2001 recession is the only to actually not have a decline in GDP.
His graphs are also retrained, keeping to a basic presentation instead of twisting data into a different, sexier, but harder to understand graph. John’s approach with restraint, clear data, and an enviable color plot shows you don’t have to use a lot of sophisticated techniques to make a good infographic.
Where are the safe areas in your city? One of the most fundamental components of newspapers has been the crime beat report. With the revolution in journalism, newspapers, non-profits, and municipalities are beginning to display the data online with interactive maps. Although the data is similar, there are several different approaches to visualizing the data.
The New York Times homicide map presents basic dots of homicides and a bar chart showing the number of homicides since 2003. Hovering over each dot shows the crime, the victim’s demographics, the perpetrator, motive, and method of crime. Users can filter by the crime date, victim and perpetrator demographics.
The Los Angeles Times uses an approach with emphasizes the neighborhood statistics. At first, users are presented with a list of neighborhoods and a search box. The Times provides a full set of neighborhood statistics, including crime, population, demographics, education, and housing statistics using the Google Chart API.This approach gives a bigger picture of the neighborhood at large—apt for residents and those wanting to move to a new place.
There are a couple of notable crime sites from Chicago. The Chicago Tribune’s crime site is also focused on the neighborhood. At first, users are provided a map with each of Chicago’s neighborhood and crime rate. Clicking a neighborhood provides a detailed list of crime statistics of major crime categories, a map shows crimes in the neighborhood within the last 30 days, and detailed list over time.
Meanwhile, volunteers built Crime in Chicago. Unlike the prior approaches, this site emphasizes neighborhood crime stats and comparing to other neighborhoods. Instead of being presented a map—like other options—users see a bar chart of crime in each neighborhood. Neighborhood statistics provides the traditional breakdown of major crime categories and a wonderful calendar chart made from D3.
Each site has similar data, but the approaches are very different. Even the creators of the Chicago Tribune site were influences by the LA Times, but the execution is still very distinct. While none of the approaches are wrong, they do seem to useful in distinct ways.
Chartwell is now available for websites. The font is quite innovative as it can render numbers into precise charts using the OpenType font system. Previously, we were limited to using Chartwell to desktop programs such as Adobe Illustrator. But now you can expand the fonts to websites, making it possible to generate plots that are compatible on every conceivable browser.
(via The Why Axis)
Capturing the immediate vital signs of the economy is hard. Economists have developed a set of economic indicators giving the current condition of the economy and the Federal Reserve Bank has their popular Beige Book. In this time, I’m certain that no one has ever accused economists of providing the information in a clear, interactive medium.
A few folks involved in Chicago’s open government initiatives have created How’s Business Chicago? to let people explore current business conditions. It is not the first website to provide details of the municipal level, but it does have the best UI and approach.
The initial release focuses on four metrics: new business licenses, unemployment, building permits, and housing foreclosures. The data is provided in three ways. First, the data is plotted in interactive diagrams using HighChart.js, with data displayed in hover boxes. Since economic data can be noisy (i.e., moves up and down a lot), trend data is also provided to give a clearer picture of the trend. Lastly, if the plot isn’t clear enough, a simple summary of the trend in a color-coded text box.
This is a great project that can be replicated in other cities. Hopefully more economic indicators will be added to this site. This project is open source so you can find the code on GitHub and the data in Fusion tables.
Earlier this week, The New York Times’ Hannah Fairfield published a wonder graph of miles driven and traffic fatalities. So I figured we should revisit an earlier, similar graphic on the relationship between the price of gasoline and miles driven. It was also created by Hannah Fairfield and uses a similar approach: using values on the x- and y-axis while representing time with meandering lines.
This graph effectively demonstrates the law of demand, but forgoing the typical graphical relationship used in economics classes. This diagram clearly demonstrates the rise in gas prices are met with reducing the number of miles driven. Moreover, we see how inelastic consumers reaction to increase in prices. Only during the recent spike in prices did miles driven bend backward. The dramatic price increases only reverted the miles driven by a few years; however, the recent surge in prices reduce miles driven to 1999 levels.
Economic graphs of this relationship can be confusing, but this graph makes it clearer than the supply and demand models in textbooks try to communicate. Likewise, it makes a point economists struggle to highlight. By increasing fuel efficiency—which reduces the per mile cost of driving—how many more miles will be driven as a result?
I feel too many data visualization folks undervalue the importance of static images. As it tends to happen, programmers like to delve into interactive diagrams, but a lot of content is still consumed through a paper medium (or at best, PDFs). Important folks are less likely to sit in front of a computer and browse and interactive report.
That is why I really appreciate the work in Andrew Fung’s portfolio. His examples are neat, crisp graphs in a printed report. This has more applicable day-to-day value than most astounding interactive graphs on the web today.
Each graph uses the proper graphing techniques (e.g., y-axis starts at zero), uses a superb color scheme, and really attempts to minimize any chart junk. One critique, however, would be to include direct labels on the chart instead of color-based keys. Regardless, it is very important that graph designers are able to produce graphs for printed reports. We are not at the golden age of mobility, so paper is still the primary medium that we still need to use.
The New York Times created a meandering plot on the relationship between road fatalities and miles driven in the United States. The per capita miles driven has doubled since 1968, but the number of deaths per 100,000 people has fallen roughly 60 percent.
The diagram is essential a scatterplot, with a line connecting each point and every year is labelled. The reader is then able to spot the trends in three dimensions: the trend in miles driven; the trend in death rates; and how that corresponds to time.
A common theme in practical, helpful graphs is a narrative interwoven with the diagram. Moreover, the approach showing the relationship of per capita miles and per capital deaths shows an interesting—and sometimes expected, for the lay reader—trends in the data. Often, these trends correspond to technological (e.g., brakes) and economic (e.g., gas prices) factors. Without that narrative, the reader would be left to conjure his own incorrect hypothesis.
The old maps from the 19th century are probably the best graphs you can find. There are complete contrast to the aesthetics you find today. The yellowish paper, hand-drawn graphs, and deep, warm colors from the printing method provide a superb look. The effort also needed to make these graphs is always gratifying since I know it took time and planning to create each graph.
A new site, Handsome Atlas, shows the pages from the U.S. Census books from the late 19th century. The U.S. was emerging from the Civil War and the Census publications became more illustrious.
The first image is a chart on the political parties in the U.S. as it relates to presidential elections. The chart is confusing, but there are some redeeming characteristics. First, it adds substantial narrative alongside the graph. The narrative does not focus on explaining the graph, but instead is a true supplement to the entire story. The graph also utilizes branch or river-like sketching within the colored region to show small sub-movements within the political parties. This is just about lost in contemporary politics, but the two-party system of yore had substantial movements which could eventually replace an established party.
The second graph looks at how individuals occupy their time. It is a tree diagram showing the distribution of people in various industries and education by state. Older charts seem almost brazen in their willingness to simplify data for presentation. It is very useful to see a simple distribution of a few key industries in a single graph.
The third graph shows the rank and change-in-rank of state populations over time. It’s reminiscent of ladder, or slopegraphs, that are popular today. In a nice, but a little confusing, bit of minimalism, the nodes terminate if there is not a change in a state’s population rank.
On the topic of population, the last image is a graph showing the distribution of the population. The western frontier is clearly visible in the graph. The color is fantastic, a intended by-product of the printing style of the time. It is unfortunate inkjets can’t reproduce the same warmth.
It is also interesting to see statistics of, as the site puts it, your great-great grandfather. There is, of course, the dated, old-timey language like “idiots” and “lunacy” graphs, but there is also substantial attention paid to oats, tobacco, corn, and wheat—this was before the American industrial revolution. The western frontier is literally visible in the maps. Political issues are also clearly apparent as they are careful to label if Native Americans and other marginalized populations are included—since their individuality was dubious at the time. Immigration was more focused on the migration from upper-European nations—a distinction that wouldn’t be made today.