Here is how to improve your charts, graphs, maps, and…

October 2, 2010

(This article was first published on Isomorphismes, and kindly contributed to R-bloggers)

Here is how to improve your charts, graphs, maps, and plots:

  • Erase non-data ink.
  • Erase redundant data ink.
  • Maximize the ratio of data to ink.
  • Show data variation, not design variation.
  • The surface area of graphical elements should be directly proportional to the numerical quantities represented.  (Don’t use 3-D bar charts, for example.)
  • Don’t lie.
  • Get as much data as you can in the first place.
  • Apply the right transformations to the data (adjust for inflation, divide to per-capita numbers, take the square root of naturally squared quantities).
  • Then, you can shrink the graphics way down.
  • Increase data density and data resolution.
  • Maximize the amount of information per unit of space.
  • Maximize the amount of information per unit of ink.
  • Above all else show the data.

For example, here’s how he would use the eraser, not the pen to improve on the typical bar chart or histogram.  (3-D bar charts are right out.)

Tufte histogram

Additionally, Tufte wants news publications to use sophisticated graphics that let the data tell their intricate story, rather than simplistic graphics that attempt to “dazzle” the viewer.

  • Like good writing, good graphical displays of data communicate ideas with clarity, precision, and efficiency.
  • Like poor writing, bad graphical displays distort or obscure the data, make it harder to understand or compare, or otherwise thwart the communicative effect which the graph should convey.

Lastly, regarding wide versus tall graphics:

  • If the data suggest a shape to the chart, follow that suggestion.
  • Otherwise, move toward graphics about 50 percent wider than tall.

To leave a comment for the author, please follow the link and comment on their blog: Isomorphismes. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , , , , , , , , , , ,

Comments are closed.


Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training


CRC R books series

Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)