![]() ![]() ** testing if installed package can be loaded from final location Installing package into ‘/home/myusername/R/scholar/4.0.0’Ĭontent type 'application/x-gzip' length 4203095 bytes (4.0 MB) Your terminal will show the build progress and eventually show whether the package was installed successfully or not. R will automatically download the package and all its dependencies from CRAN and install each one. Now install the desired package using the command install.packages('package_name'). Read the documentation for the package to identify which modules should be loaded. So, you will need to load the corresponding modules before installing sf. For example, the sf package depends on gdal and geos libraries. However, some R packages depend on other libraries. (if needed)įor simple packages you may not need this step. Otherwise, move to the next step to install the package. If the package you are trying to use is already installed, simply load the library, e.g., library('units'). You can check if your package is already installed by opening an R terminal and entering the command installed.packages(). Step 1: Check if the package is already installed.Īs part of the R installations on community clusters, a lot of R libraries are pre-installed. If you have created a ~/.Rprofile file previously on Scholar, ignore this step. Link to section 'Installing Packages' of 'Installing R packages' Installing Packagesįollow the steps for setting up your ~/.Rprofile preferences. For your convenience, a sample ~/.Rprofile example file is provided that can be downloaded to your cluster account and renamed into ~/.Rprofile (or appended to one) to customize your installation preferences.You can define the directory where your R packages will be installed using the environment variable R_LIBS_USER.So, libraries for each R version must be installed in a separate directory. Each cluster has multiple versions of R and packages installed with one version of R may not work with another version of R. ![]() So, if you have access to multiple clusters, you must install your R packages separately for each cluster.
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