I am a huge fan of the R language for statistics and graphics.
I sometimes hear people say they don’t like R but then admit that they have never tried to use it, or if they have it was close to ten years ago (and a lot has changed).
In recent discussions at work I got the impression some people have got a bit predjudiced against R and other software that they don’t actually use, primarily because of the added difficulty of software that requires a bit of programming.
I think that multi-disciplinary work will inevitably mean we find a mix of software in use, and they’ll all have strengths and weaknesses. A major strength of R is that one can weave together a report that includes the data, code, graphs and interpretations for an analysis, rather than copy-and-pasting these elements together as is required with other software toolboxes.
For example a simple analysis in Rstudio using the ‘R Markdown document’ is below.
You can load and explore data in the document by placing ‘Code Chunks’ in the document, then when you click the Knit HTML button a web page will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
summary(cars) ---
| speed | dist |
|————–|—————-
| Min. : 4.0 | Min. : 2.00
| 1st Qu.:12.0 | 1st Qu.: 26.00
| Median :15.0 | Median : 36.00
| Mean :15.4 | Mean : 42.98
| 3rd Qu.:19.0 | 3rd Qu.: 56.00
| Max. :25.0 | Max. :120.00
—
You can also embed plots, for example:
plot(cars)
I hope we can work toward a kind of ‘tower of babel’.
