The Visual Display of Quantitative Information

What Hacker News says

1. FarmadupeSep 2026
   I'd actually recommend some excellent books on the "philosophy" of data presentation: The first that comes to mind is "the visual display of quantitative information" by Edward Tufte seems to be freely available online, and the other one on my mind is "how charts lie" by Alberto Cairo (which doesn't seem to be freely accessible)

   But if it helps, just some "initial gut feel observations" from me:

   * It's definitely not possible to find issue with the the _sheer amount_ of results, but there's just far too much for a human to absorb, all presented at once

   * Overall text size is quite small, and difficult to read

   * The page doesn't make a strong statement of _what_ is under test: the first words are: "modern-fs-benchmark Multi-device CoW filesystems under workloads classic benchmarks skip" -- which defines the webpage in terms of what it is _not_, without stating what benchmarks are actually present.

   * The first line of teh page contains run statistics that probably eithre want to b at the bottom, or just don't need to be in the webpage at all: "latest run 2026-09-18 18:50:45 UTC, kernel 7.0.0-1012-azure, 593 runs recorded · 145 trend points shown"

   * A significant proportion of the free text is caveats. There's nothing wrong with being transparent about limitations, but they may be a sign that there might be alternative ways to present the data, or that the data may be flawed (depending on the caveat)

   * Theres several categories that I think have been invented for the purpose of collation, but I don't think are defined on the page. I think "Overall Core" and "Core I/O" aren't explained, which means by definition it's impossible for a reader to understand the score table.

   * And as we're all aware right now, current Claude models are currently struggling to write coherent English. There's several incoherent sentences on the page. It's a Claude issue.

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2. tem_alThorJun 2026
   https://github.com/temataro/better-graphs

   I want to teach good Matplotlib taste to agents and humans. This repo contains: 1. Agent instructions + design motifs (Claude Code skills + a CLAUDE.md). 2. An online "blog" tutorial of the same skills, for people. 3. minerva.mplstyle, my opinionated sane matplotlib defaults.

   Inspired by Tufte's book: The Visual Display of Quantitative Information (a gift from my boss!), plus data-to-viz.com and the python-graph-gallery. Aiming for halfway to the gorgeous plots in the paid matplotlib-journey.com, but free and open to share with friends. :)

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3. tem_alThorJun 2026

     This repo is three things in one:
     1- A set of instructions and design motifs AI agents can incorporate into their understanding of what makes a good Matplotlib graph through SKILLs and a CLAUDE.md.
     2- An online 'blog' tutorial for a human audience to learn the same skills (to remind me how to do specific things or teach an intern/coworker the same idea).
     3- An included mplstyle file that contains my opinionated set of sane default configurations for matplotlib: minerva.mplstyle.
   

   My biggest inspiration was Tufte's The Visual Display of Quantitative Information which my boss gifted me a couple years ago, data-to-viz(dot)com and the python-graph-gallery were the big references for "which chart for which data", and to be fair those are by the same author as a paid course I couldn't justify paying for to myself called matplotlib-journey(dot)com. My is to try to get half the way to the amazing plots they show you but free, open-source so I can share it with friends

   I'd genuinely be interested just to use this post as a way to survey the HN community on what things levelled-up your own Matplotlib graphing or what finally made general science/quantitative data communication click.

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4. groby_bFeb 2026
   That's somewhat unfair to the site - they are very much still exploring how to visualize information understandably and aesthetically pleasing. Yes, they got started when infographics got really popular, but it's very much a site that's alive and continuing its work.

   And really, infographics are rooted in information design. Which in itself is much older than the web. Heck, the canonical popular book - Tufte's The Visual Display of Quantitative Information - is from 1982.

   I know it's not the most popular thing if you can just ask Claude for a quick visualization, but the space is both very rich in information LLMs blissfully ignore, and continues to be fertile ground for explaration.

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5. xnorswapApr 2025
   Sparklines are not bar graphs, they're lines, hence the name. If you have a copy of Tufte*, you can find them on page 171.

   Tufte has written up a history here: https://www.edwardtufte.com/notebook/sparklines-history-by-t...

   This tool doesn't really create sparklines, but it does create small charts, although given it is delivered via custom font, it's usefulness is limited.

   * And anyone interested in displaying information is doing themselves a disservice without a copy of "The Visual Display of Quantitative Information" by Tufte.

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6. philsnowFeb 2025
   The first image jumped out at me because the author chose to use blue and red which, when used on a map of the United States always indicates political affiliation, but the areas that were marked "red" and "blue" were reversed from what my expectation was (coasts and cities red, midwest + great plains blue).

   > A county like San Francisco or New York, which packs thousands of residents into a small area, now stands out with an intense color saturation, drawing the eye immediately to where the people actually are. Conversely, a vast county with a sparse population adopts a lighter tone, accurately reflecting its lower density without the distraction of an oversized area.

   (Emphasis on "saturation" added.) This isn't quite right, the most-densely populated hexes (large cities) are a pretty saturated red color yes, but the least-densely populated hexes (west Texas) are a pretty saturated blue color. In fact, this color palette makes it really difficult to see what the author intends.

   > Using the size of counties as a dimension to represent population can also showcase population centers and free up the color dimension to show another dimension like population density.

   Ok yeah that's a cartogram, I know how to expect that to look... wait, no, the image has the same center points for every county, a hexagon outline drawn around that, and then a confusingly-colored solid circle painted over each. The colors are confusing because the overwhelming effect is that the hex outlines dominate the perception of the dark blue nearly-point-sized "circles" in the majority of the map.

   Look at Nevada. On the first map Clark County (where Las Vegas is) is a light blue colored hex in a state of mostly dark blue hexes and Washoe County (where Reno is) is light red. On the second map Clark is the largest light blue circle in the state and Washoe is a smaller light blue circle, which seems to be the reverse of what the first map says. ...Also, Washoe appears to be in a different place maybe? It seems to have moved north a hex.

   I'm not just picking nits, this is difficult stuff, but an extremely powerful way to convey a ton of densely-packed (no pun intended) information, when done right. See, for instance [0][1][2][3] all by Edward Tufte.

   [0] "The Visual Display of Quantitative Information" https://www.amazon.com/Visual-Display-Quantitative-Informati...

   [1] "Visual Explanations: Images and Quantities, Evidence and Narrative" https://www.amazon.com/dp/0961392126

   [2] "Beautiful Evidence" https://www.amazon.com/dp/0961392177

   [3] "Envisioning Information" https://www.amazon.com/Envisioning-Information-Edward-R-Tuft...

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