The grammar of graphics

What Hacker News says

1. graphvizJan 2024
   This is interesting and a little bit entertaining.

   There has been excellent work on taxonomies for data visualization. Tamara Munzner's book "Visualization Analysis and Design" is a good starting point.

   There has been excellent work on identifying "dimensions" or properties of data visualization. Lee Wilkinson's "Grammar of Graphics" is a landmark. You could search backward to find Bertin's Semiology of Graphics, or forward to find ongoing work like UW's Vega https://idl.cs.washington.edu/papers/vega-lite/

   Some of this work might somewhat capture the properties of a periodic table to organize a catalog and even support further discovery.

   Show morethread
2. sargstuffSep 2022
   Plenty of visual tropes from various software example galleries.

   If weren't for the 2d/3d limitation, would have gone with https://flowingdata.com/2019/10/08/visualization-gifs-imagem... instead of the stata-mation stuff.

   * Chart types :

      * latex-cookbook.net : https://latex-cookbook.net/
   
      * ggplot2 gallery :  https://exts.ggplot2.tidyverse.org/gallery/  https://plotnine.readthedocs.io/en/stable/gallery.html
     
      * "ggplot2: Elegant graphics for data analysis" : https://ggplot2-book.org/
   
      * Rstudio gallery : https://community.rstudio.com/c/table-gallery/64
   
      * https://flowingdata.com/chart-types/ && https://flowingdata.com/category/tutorials/
   
      * https://reference.wolfram.com/language/guide/StatisticalVisualization.html
   
    

   ** xkcd like stuff:

     ** food for thought : https://flowingdata.com/2016/12/12/calories-in-fast-food-menu-items/
   
     ** heat map in excell : https://flowingdata.com/2020/09/29/how-to-make-a-heatmap-in-excel/
   
     ** juggling the statistics : https://flowingdata.com/2015/12/15/a-day-in-the-life-of-americans/
   
     ** https://flowingdata.com/category/projects/data-underload/
   
   

   ** xkcd NLP approach :

     ** https://flowingdata.com/famous-movie-quotes-as-charts/
   
     ** https://flowingdata.com/2010/05/26/famous-science-fiction-quotes-in-graph-form/
   
     ** http://www.visguy.com/2010/05/27/sci-fi-movie-quotes-visualized/
   
   

   ** General composibility techniques with examples:

      ** "The Grammar of Graphics" by Leland Wilkinson
   
      ** R for Data Science : https://r4ds.had.co.nz/data-visualisation.html
   
      ** "Visualize This: The FlowingData Guide to Design, Visualization, and Statistics" : https://book.flowingdata.com/
   
      ** Flowing data : https://flowingdata.com/2020/09/08/telling-stories-in-visual-data-driven-essays/

   Show morethread
3. jstx1Dec 2021
   The thing that's specific to data visualisation is the problem of mapping properties of your data to properties of the visualisation. Some good resources on this are

   The Visual Display of Quantitative Information - Edward Tufte

   The Grammar of Graphics - Leland Wilkinson

   FlowingData's guides - https://flowingdata.com/category/guides/

   But from your list I gather that you're more interested in the visual design of things (colour schemes, fonts etc); if that's the case you can search for resources on visual/graphic design which I don't know too much about. I can say that the choice of fonts and colours is a small part of data visualisation - very few basic princpiples, using a tool with good defaults and some common sense get you a very long way. The bigger part is deciding which parts of your dataset to communicate in what way and the resources that I mentioned are pretty good at teaching you that.

   Show morethread
4. ingqondoMar 2021
   ggplot2.

   The 10X was not just that it made it easier and faster to make exceptionally beautiful plots. Rather it was that it made me realize for the first time that software was, fundamentally, about an implementation of ideas. That the underlying idea, together with how well it's communicated through the API design and documentation, really matters. Reading Wilkinson's description of the grammar of graphics, and then seeing that translated to a code library... That was amazing. It defined what I think software is, as someone who was new to the world coming from an engineering background where coding was just an easy way to do linear algebra.

   Show morethread
5. wkmeadeMar 2021
   1. Power Query/Pivot Tables/Power Pivot Directly connecting to SQL from Excel for data exploration 10x for me. Personal record is 77,000,000 rows in Excel via Power Pivot. Lining up count vs count distinct on year-week is my go to garbage data detector. Weather data suppliers have an unseemly habit of over as well as under reporting. :-) 2. SYGRAPH, the data visualizer Lee Wilkinson to accompany SYSTAT, before he wrote THE GRAMMAR OF GRAPHICS which we now now as ~ggplot2 3. NT 3.51 - the first vision of what a stable workstation could be 4. SSDs "20 times faster" but non-users can't process the meaning of those 3 perfectly good English words
   Show morethread
6. spectramaxJul 2019
   I agree. Infographics and the like are a cancer to the graphics world. I want data in its most simplest form, digest it using simple semiology and graphical grammer and move on. I find Cleveland et. al (Visualizing Data), Jacques Bertin (Semiology of Graphics) and Leland Wilkinson (Grammar of Graphics) much more 'scientific' in their approach than Tufte. Reading Tufte's books is akin to reading Josef Alber's - Interaction of Colors, which btw is the gospel of color theory amongst artists and designers: They provide interesting view of the problem but not the solution to the problem. They are coffee table books in my opinion - bedazzling and extremely interesting but useless in practice. Read Edwin Land (Kodak scientist) if you want to understand color theory.
   Show morethread