Data in Heels

[mapsontheweb]

United States’ 8 million miles of roads, streets and highways.

[tabletopwhale-deactivated201910]

I’m excited to finally share a new design project! I’ve designed a collection of ten astronomy maps built on open data. Over the next few weeks I’ll share each map alongside open-source code and tutorials. Up next week: a map of everything in the solar system bigger than 10km!

[deeplylearning]

Guys, I’ve found my new favorite data viz blog (who also has a Tumblr!). She is a biology PhD candidate who creates scientific data visualizations for all topics of science. Check her out!

[990000]

simongerman600

[brunhiddensmusings]

i was going to say ‘i have no idea what to do with this information’ but then i realized its a handy guide to generate fake words that sound english

[vacuously-true]

@the-real-numbers

Think you can math up some fake words that sound English? I believe in you!

[the-real-numbers-deactivated202]

So first of all, I have no real idea what these stats are or if it’s P(char|index) or P(index | char).

So I computed letter frequency (y-axis) by index (x-axis) myself and now I have both.

(These plots are zero indexed. I used Peter Norvig’s “big.txt” corpus.)

[mapsontheweb]

Tree Diversity in the United States.

[the-real-numbers-deactivated202]

What the heck is up with Tate’s Hell State Forest

[deeplylearning]

I would definitely inverse the color key on this map to follow data visualization best practices. Because one thing that I immediately thought of is…

… California has a lot of forest fires. Is that somehow related to lack of diversity in trees? Or is the weather just THAT different that any tree would burn down, so the few species in California are actually the superior ones?

Also, is the diversity in the east coast actually a bad thing due to invasive species? Does that make the ecosystems weaker or overall stronger? That actually makes me think that maybe the coloring actually IS appropriate if diversity is considered bad in this context. Yet they used the positive term “richness” to describe high diversity… Hmm.

This data visualization is not self-explanatory at all.

Biologists/Ecologists, explain

[datainheels]

So basically this is an example of a BAD data visualization. People think maps are cool, and they can be, but there’s barely any context to this visualization that it can be interpreted in a WILD variety of ways that I just explained above (among others I probably didn’t think of).

I want to point out that cultural differences and other personal experiences can make people look at visualizations, or even interpret data (and thus manipulate it into visualizations) in different ways.

For example, the color red signifies good luck in a place like China, but in the US red is a “bad” color. But the fact that the creator of this visualization

made this visualization in English

used a negative (to English-speaking countries) color

and described it with a positive word like “richness”

... is the reason this visualization is so confusing and doesn’t really make any sense. Because the cues to meaning are contradictory.

Just because it’s pretty doesn’t mean it’s effective.

You can technically read the graph (red = high diversity) but it doesn’t have any actual meaning. What does it mean to have high diversity??? I don’t know. That was supposed to be the job of the person who visualized this data. F-

[mapsontheweb]

The Herds of Europe: grid bubble maps of EU livestock distributions.

[datainheels]

How Music Taste Evolved

Every top 5 song, from 1958 - 2016, so we can stop arguing about when music was still good

THIS PLAYS THE TOP SONG AS THE GRAPH MOVES THROUGH TIME, IT IS SO COOL!!!!!!

And nostalgia-inducing.

[datainheels]

The Largest Vocabulary In Hip Hop

Rappers, ranked by the number of unique words used in their lyrics. It compares the number of unique words used by some of the most famous artists in hip hop (that is, an example of a quantitive view of lyricism, once proposed by Tahir Hemphill). I used each artist’s first 35,000 lyrics. This way, prolific artists, such as Jay-Z, can be compared to newer artists, such as Drake.

Check out the interactive visualization here.

[datainheels]

Infogram Customer Spotlight: The Best Data Visualization Tips and Award-Winning Reports from HackerRank - Infogram

See how HackerRank builds reports and guides that blend data and design with Infogram. Bonus: get their pro data visualization tips.

[datainheels]

The 45 Best — And Weirdest — Charts We Made In 2018

Another year, another few hundred charts and maps on FiveThirtyEight. (Not to mention our interactive graphics and updating dashboards.) To celebrate the end of…

[datainheels]

The Rhythm of Food

How do we search for food? Google search interest can reveal key food trends over the years. From the rise and fall of recipes over diets and drinks to cooking trends and regional cuisines.

Explore the interactive visualization here.

[datainheels]

Gun Deaths in America

This interactive graphic is part of our project exploring the more than 33,000 annual gun deaths in America and what it would taketo bring that number down. See our stories on suicides among middle-age men, homicides of young black men and accidental deaths, or explore the menu for more coverage.

Explore the data visualization here.

[datainheels]

Where People Run in Major Cities

There are many exercise apps that allow you to keep track of your running, riding, and other activities. Record speed, time, elevation, and location from your phone, and millions of people do this, me included. However, when we look at activity logs, whether they be our own, from our friends, or from a public timeline, the activities only appear individually.

What about all together? Not only is it fun to see, but it can be useful to the data collectors to plan future workouts or even city planners who make sure citizens have proper bike lanes and running paths.

Learn more about this project here, including how to map your own paths.

[datainheels]

Keuzestress – Searching for the ‘correct’ mascara

I once again found myself experiencing ‘keuzestress’ which is the Dutch word for choice stress. You see, I would like to buy myself some mascara. I would like to pick one that suits my needs. But considering I never was a very girly girl and I mostly go out without any makeup (“Nooo! You actually do that?!”) I’m not that experienced in picking the correct one. If there ever is such a thing. When I go to a shop and see all those brands recommending all their products I just go blank. There’re just too many of them.

Learn more about this visualization here.

[datainheels]

What Happens to the Plastic We Throw Out?

How a piece of trash can travel from land to Henderson Island, an uninhabited, remote island in the middle of the South Pacific Ocean

See the full interactive visualization here.