Whenever I speak with students, I emphasize the need to share as much code and data as is feasible to enable reproduciblity. The fact that a large amount of research is not reproducible is a big issue that has gotten a lot of traction in the past two decades since Ioannidis published his influental paper.
One of the coolest packages for R is knitr. Essentially, it allows you to combine explanatory writing, such as a paper or blog post, directly with your analysis code in a Markdown document. When the target document is compiled (‘knitted’), the R code in the document is run and the results inserted into the final document. The target document could be an HTML or a PDF file, for example. This is great for many reasons. You have a regular report you want to run, but the data updates? Just re-knit and your entire report is updated. No more separate running of the code followed by copying the results into whatever software you use to build the report itself. This makes it not just less cumbersome, but less error prone. It also improves reproducibility. Somebody wants to see your work, perhaps because they are unsure of your results or they want to extend your work? You can share the markdown file and the other party can see exactly what code was used to generate what part of your report or paper. ...