This is my first response here, so I'm not sure if I should have replied to Vincent's recent response with excellent suggestions, or the original email (?). I opted for the latter. Please let me know!
> Forth issue: > > At 20:39 in the video, he speaks about ?plot and help functions in R. In > RStudio this help information opens up in a separate window, but in > Emacs this information is shown in the same buffer as used for the > regular tasks. What settings should I put in order to get this help > information presented in a new buffer. I would prefer to have the > following setup. .R file in an upper buffer, the *R* in the lower > buffer. When opening ?plot, I woul like the lower buffer to split and > the ?plot information being presented on the right hand. The buffers can be specified to mimic Rstudio's window configuration actually. The ESS manual contains a skeleton that you can modify (https://ess.r-project.org/Manual/ess.html?sa=X&ved=2ahUKEwiEnrnR7f7mAhVJqJ4KHaxaAK4QFjAAegQIABAB#Controlling-buffer-display). > Third issue: > > At 16:25 in the video he speaks about Pacman, as a way to manage add-on > R packages. He speaks that the add-ons are necessary to 'load' in order > to function. In what way is this done in ESS? Do I have to 'load' > packages before I used them or are they already available and ready to > use? How does this work? I should say here that I download packages > through Melpa. Probably also noteworthy to look into docker (https://www.rocker-project.org/). > Fifth issue: > > At 30:40 in the video he speaks about creating a table and in RStudio he > is able to run the following entry (cylinders <- table(mtcars$cyl)) and > then get to see information about name, type, length, size and value of > the table in the top right corner of RStudio. Is this possible to do in > ESS as well in a similar wy? Which command should I use to get to see > this info? Work off Rmarkdown documents using polymode and ESS, or open up an R script and hit C-c or C-enter to execute blocks or lines of code. This will open up the corresponding R interpreter and you will see the output as you see the console output in R. You could start up Mx-R if you really want or optionally start with an Org mode document with source code blocks like the following may be the minimum you require. You could also paste the code within the block headers below into an R file and execute. I typically have all my code in Org mode documents that I tangle into .R scripts or other source code like Dockerfiles. #+BEGIN_SRC R # Easy packages just makes the syntax easier to load and install packages in batch install.packages("easypackages") # Install the tidyverse metapackage. Add other necessary packages here # as ("tidyverse", "package-name1", "p2"). You may need more installed. packages("tidyverse") # Call up the installed library library("tidyverse") # Add your command here #+END_SRC > These were the questions I had at the moment. Would be very grateful for > help! By the way, are there any instruction videos of ESS? Reading and > understanding the manual is not so easy and searching through issues > that have been discussed before on your site was very tricky, .... It is hard to get an overview very quickly. I have captured some notes on my website : https://shreyas.ragavan.co/docs/ess-datascience-r/ . These are far from comprehensive or gospel in any form, and I am yet to push updated notes. However, the keyboard combinations are certainly things that I use very frequently and it should be useful as a supplement. ______________________________________________ ESS-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/ess-help
