data visualisation

A new write-up takes a fresh look at Edward Tufte's data-ink ratio, the influential data-visualisation principle holding that charts should maximise the ink devoted to data and minimise everything else. The piece unpacks what the ratio actually means, where it is often misread, and how far designers should take it in practice. Readers in the data and design community are weighing in on whether the classic guideline still holds up.

A developer has expanded the Chart View functionality in a market analysis tool, while noting some hesitation about the work. They say they are not a believer in charting as a method and acknowledge many existing programs draw better charts, but argue that a picture still conveys information effectively. The update reflects an ongoing effort to improve how users visualise market data.

A new website called Awesome Dataviz has launched, ranking data visualisation libraries and tools on a daily basis using metrics drawn from GitHub, NPM, PyPI and CRAN. The launch was shared on Hacker News as a Show HN post, drawing modest engagement with a small number of points and few comments so far.

Kepler-1314 b is a Neptune-like giant exoplanet located 463 light-years from Earth. Discovered in 2016 by NASA's Kepler telescope, it has a radius about 5.11 times that of Earth and completes an orbit in just 5.42 days. Astronomy communicators are sharing the planet's profile alongside NASA's Eyes on Exoplanets visualisation, drawing renewed attention to the Kepler mission's catalog of worlds beyond the solar system.

A new write-up examines Edward Tufte's well-known data-ink ratio, the principle from 'The Visual Display of Quantitative Information' urging designers to maximise the ink devoted to data and strip away chart decoration. The piece reframes the idea as 'Tufte's Razor' and walks through what the ratio actually measures and how to apply it in practice when designing charts and visualisations.

A new website called Awesome Dataviz ranks data visualisation libraries and tools daily, drawing signals from GitHub, NPM, PyPI and CRAN. The project was shared on Hacker News by its creator, Javier Luraschi, inviting feedback from the developer community. The rankings aim to help developers and analysts discover which visualisation libraries are currently gaining traction across the main open-source package ecosystems.

A new website called Awesome Dataviz has launched, ranking data visualisation libraries and tools each day based on activity across GitHub, NPM, PyPI and CRAN. The launch was shared as a Show HN submission, where it drew modest early attention from the developer community, with commenters weighing in on the usefulness of daily cross-ecosystem rankings for picking charting and plotting libraries.