R Utilities

Link: R

Update R, install packages and check version §

Check R version §

## Check R version
R.version
## Check R home path
R.home()

Update R in R GUI §

install.pacakges("installr")
require("installr")
updateR()

Error handling §

If encounter security issues:

1. Disable secure download setting by: Uncheck “Use secure download method for HTTP”
2. Use below argument to install and update R in R GUI

    install.packages("installr",dependencies = TRUE, repos = 'cran.rstudio.com/')
    ## Then update by specifying the cran repo
    installr::updateR(cran_mirror = "cran.rstudio.com/")

(Optional) Change library path §

Add following to RProfile:

myPaths <- .libPaths()   # get the paths
myPaths <- c(myPaths[2], myPaths[1])  # switch them
.libPaths(myPaths)  # reassign them

From www.accelebrate.com/library/how-to-articles/r-rstudio-library

Install R packages §

install_packages(c("tidyverse", "openxlsx"))

How to install tinytex offline §

## From <community.rstudio.com/t/cant-install-tinytex-properly-via-install-prebuilt/28476>
tinytex::install_tinytex
tinytex:::install_prebuilt("install.zip")
tinytex:::is_tinytex()

Check installed packages §

## From <stackoverflow.com/questions/38481980/get-the-list-of-installed-packages-by-user-in-r>
x <- installed.packages(); x[ is.na(x[,"Priority"]), c("Package", "Version")]

Close all data view windows in RStudio §

CloseViews <- function(){
    cmd <- paste0('wmctrl -c "Data:" -v')
    ok <- TRUE
    while(ok){
        out <- suppressWarnings(system(cmd,intern=TRUE,ignore.stderr=TRUE))
        Sys.sleep(0.2)
        ok <- is.null(attr(out,"status"))
        print(ok)
    }
}

Then CloseViews() does the trick, which I found particularly helpful when working interactively.

From <stackoverflow.com/questions/14349868/programmatically-close-the-window-created-by-viewx>

Purl: convert R Markdown to R Script §

knitr::purl("purl.Rmd")

From <bookdown.org/yihui/rmarkdown-cookbook/purl.html>

Convert backslash for Windows system §

Copy file path, then run:

gsub("\\\\", "/", readClipboard())

Best practice: reduce the number of objects §

The way is to create dataframe list.

dl <- list("f21" = df, "month" = df_month)
rm(df, df_month) ## to keep it clean

When refer object from dataframe list:

dl$f21
dl[['f21']]
dl[[1]]