Category "Visualization"

D3 in Depth:

D3 in Depth aims to bridge the gap between introductory tutorials/books and the official documentation.

I have found D3 extremely useful for creating dynamic plots on dashboard style websites for monitoring data pipelines. This looks an excellent resource for learning it.

via FlowingData

Colorgorical is an alternative to ColorBrewer with a few different options for creating color tables. For example, you can add a couple specific colors that should be in the color table and let Colorgorical figure out the others which maximizes the perceptual difference between the colors. Colorgorical seems particularly well suited to generating qualitative color tables, e.g., to find sufficiently different colors for each line in a plot.

via FlowingData.

Motivated by the below chart of the age distribution of Olympic athletes, Junk Charts presents several techniques to visualize multiple distributions:

Age distribution of Olympic athletes

Candidates include the traditional boxplots used by statisticians as well variations and a stack of histograms. I think violin plots, suggested by a commenter, are a nice compromise showing the full distribution.

John Nelson produced this beautiful map of how the boundaries of US droughts have changed over the last five years with data from the US Drought Monitor:

Link via FlowingData.

Part 2 (of what promises to be a four part series) of the great comparison of Google Maps and Apple Maps by Justin O’Beirne. See part 1 before starting with part 2.

This is an example of using a clever color key that doubles as a histogram showing the distribution of the corresponding areas.

By the way, this post is from a great series about small ways to make better visualizations.

Nice example of why rainbow color tables can be misleading:

Regular readers will be aware of the #endrainbow campaign to reduce the use of rainbow colour palettes in scientific figures. At the recent EGU conference, I gave a talk on ‘making better figures’, which included an example of a published conclusion which was incorrect due to the use of a rainbow colour scheme.

via @asoconnor via @rsimmon

This is a great article about the change in balance between cities and roads in Google Maps between 2010 and 2016.

He also compares Google Maps versions to an old printed map:

Even though it’s from the early 1960s, the old map is more balanced than the Google map.

There are a lot of visualization lessons to be learned from cartography.

This is a great idea to visualize the punctuation in novels:

Inspired by a series of posters, I wondered what did my favorite books look like without words. Can you tell them apart or are they all a-mush? In fact, they can be quite distinct.

Robert Simmon redesigns a graphic:

Creating scientific graphics can be difficult: most scientists and engineers lack training in design, deadlines are tight, compromises must be reached between team members and management, and the available tools may be limited. Fortunately, many design guidelines are simple and easy to execute, which I’ll show by re-designing the following graph, originally presented by NASA at the 2015 American Geophysical Union fall meeting.

I would not have removed the inset map of the region because I thought it added useful visual context to the exact lat/lon location in the subtitle, but maybe that is just my unfamiliarity with that area. I also wondered what the graphic would look like if it used a Brewer diverging color table for the colors in each band instead of red for all positive values and blue for all negative values.

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