Rstudio Install [REPACK]

So a relatively simple question, usually when you saved an R script that you had opened in RStudio you will get prompted with a banner above the script saying that there are packages not currently installed that are required for that script (or something to that effect). However that is no longer the case, is there any way to force RStudio to check if packages are installed and if not then to install them? Also, What happened to this feature? How can I re-enable it? I've had this issue on 3 different PCs and it is getting really annoying to manually install different packages every time. Thanks!

Thanks for your help! I did not know this was an option, I do have it enabled though. I am also using 1.3.1093 of RStudio. My guess after investigating for a bit is that it may have something to do with where R is installed R 3.6.X was installed in program files where as R 4.0.X is installed in the documents folder (I don't know why this happened as I did the same installation process I always do). Exactly why would RStudio not recognize that there are no packages installed I don't know.

Rstudio Install

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RStudio is a free, open source Integrated Development Environment (IDE) for R. RStudio is available under GNU Affero General Public License (AGPL). You can use RStudio with Oracle Machine Learning for R, however RStudio is not included with OML4R. If you want to use RStudio, you must install and license it separately.

We need to install two things onto your computer. The first is R, this is the programming language we will use. After that we need to install RStudio, this is a front end program that lets you write R code, view plots, and do many other useful things.

Prior to using the tensorflow R package you need to install a version of Python and TensorFlow on your system. Below we describe how to install to do this as well the various options available for customizing your installation.

Note that this article principally covers the use of the R install_tensorflow() function, which provides an easy to use wrapper for the various steps required to install TensorFlow. You can also choose to install TensorFlow manually (as described at ). In that case the Custom Installation section covers how to arrange for the tensorflow R package to use the version you installed.

This will provide you with a default installation of TensorFlow suitable for use with the tensorflow R package. Read on if you want to learn about additional installation options, including installing a version of TensorFlow that takes advantage of Nvidia GPUs if you have the correct CUDA libraries installed.

I've spent the last two days trying to find a workaround for this. I've updated my R (4.1.2) and have deleted and reinstalled multiple times. I have also deleted the Bioconductor package and reinstalled but this has not worked. I'm using a MacBook Pro M1 (2021).

What happens if you you say "Yes" to the question about installing from sources? Does it do anything? If you have the necessary software e.g. compilers from Xcode I'd expect this to work, but it will require those additional tools.

An alternative is to use the Mac version of R for Intel CPUs and run it with Rosetta. Bioconductor build binary packages for this platform and you should be able to install whatever package you like without requiring any additional software. From what I've read there's no discernible speed difference between using the Arm and Intel versions of R on a M1 processor, so buy picking the Intel version you gain compatibility without really sacrificing anything.

Just to add to Mike Smith's answer: the problem is almost certainly that you have installed the arm64 version of R, but Bioconductor does not support binary package builds for that version of R. You will find that you can't install any Bioconductor packages, at least not without becoming a Fortran/C compilation expert. To solve this, you need to install the intel version of R instead. On this page:

The information at -project.org/bin/macosx/ can help you install Bioconductor packages using the "arm64" version of R if you like. You will need the Xcode toolset installed, and you will have to attend to the following, extracted from the link just given:

As the respondents above note, if you use the intel-emulating version of R, you can avoid the xcode/gfortran installation and receive precompiled binaries for Bioconductor packages with BiocManager::install.

This updates the internal package cache with the info from the new source we added, then upgrades all the packages that are currently installed that have an update available. Then finally we install R itself.

Installing Quarto from a .deb file places the quarto binary at the default location. This method only supports installing a single version to the default location. You can specify a version, or easily install the latest version.

These instructions install Quarto from release archives (i.e., .tar.gz files), which lets you install it to a custom location. This makes it possible to install multiple versions concurrently. However:

In Workbench, RStudio Pro sessions have Quarto available by default. To use Quarto in VSCode or JupyterLab, you will need to either symlink or install Quarto into a location on the PATH for those editors.

If you installed Quarto1.1.189, 1.2.475, and 1.3.450 to a Connect server, then you may configure Connect with all three versions of Quarto by providing multiple Executable options to the Quarto section of Connect's configuration file.

In an environment where you intend to only maintain a single installation of Quarto, you can install Quarto from a .deb file. This places the quarto binary at the default location, /usr/local/bin/quarto, which automatically makes the quarto command available on the default PATH.

Quarto must be installed on your system before configuring Connect to allow support for Quarto content. Complete the installation procedures above and then review the following sections of the Posit Connect Admin Guide:

Two days ago I reinstalled NixOS. I am on the 23.05 channel. Apart from my attempts at adding R packages, the only changes I have made to the configuration.nix is adding applications to the environment.systemPackages = with pkgs;, and adding mullvad-vpn and syncthing as services.

If, after doing the previous changes, I run within RStudio install.packages("tidyverse") and install.packages("snakecase"), some of the dependencies are installed and can be used in RStudio. However, not all packages are installed.

Additionally, if I try to install those dependencies manually, I get the very same errors that are displayed above. In other words, if within RStudio I run install.packages("xml2"), I get the same error as above.

The rstudioapi package is designed to make it easy to conditionally access the RStudio API from CRAN packages, avoiding any potential problems with R CMD check. This package contains a handful of useful wrapper functions to access the API. To see the functions that are currently available in the API, run help(package = "rstudioapi")

Whilst its eminently possible to just use the base installation of R (many people do), we will be using a popular Integrated Development Environment (IDE) called RStudio. RStudio can be thought of as an add-on to R which provides a more user-friendly interface, incorporating the R Console, a script editor and other useful functionality (like R markdown and Git Hub integration). You can find more information about RStudio here.

I still do not understand how flathub handles build processes. I assumed that it builds flatpaks aautomagically if somebody provides the manifest. And in my understanding Alexander Wilms has provided the manifest, so there should be some RStudio flatpak on flathub, which I cannot find, but I might be missing the point. Also I did not succeed in building a RStudio flatpak with the manifest of Alexander Wilms provided here: -Wilms/flathub/tree/rstudio but maybe someone with a better understanding of flathub/flatpak build process could help.

Remember that we talked about updating what packages are available on a server? We can add a new server here pointing to the most up to date version of R. R actually maintains a server with which you can keep R in Debian up to date. To make Debian use this server you need to do two things. Add it to the list of servers Debian checks when you run apt-get update, and authenticate the server ensuring nobody can hijack it and install malicious stuff from there. (Linux is pretty secure from this perspective.) To do these we need to install a few other things we will use in the process.

RStudio must be manually downloaded from the RStudio website and installed also manually. So go to the RStudio website and download the free RStudio Desktop for Debian 11. (Same version for Ubuntu. You may see it listed as Ubuntu/Debian.) Link at the time of writing is here:

Et voil. RStudio is installed. It should be in the list of Chromebook icons called Linux apps. Run it from there. If you are going to use RStudio regularly, I would pin it to the shelf on the bottom. And again, you will not have to (often) do anything in the Linux terminal. There are minor exceptions I will list below. Once you verified RStudio works, you may also want to delete the deb package you installed it from before you close the terminal. Keeping that is a waste of space.

In sum, Chromebooks are just fine to run R. And Linux is generally a good platform for most quant work. Chromebooks give you a full Linux install which is an extremely flexible tool for data science. Many people opt to use just Linux for their data science needs. With a Chromebook, all that power is available at your fingertips on demand while you have a pretty simple to use computer where the tech and the platform does not get in the way of your day to day computing tasks.

MacTeX installs many of the things needed to use TeX for typesetting. Click on this link to download MacTeX: -bin/mactex-download/MacTeX.pkg. This is a large file and may take five minutes (or more, depending on your internet connection) to download. More information is available here: -download.html. ff782bc1db