[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**Isomorphismes**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

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.)

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**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.