The goal of this tutorial is to list all the installed packages and list all the loaded packages. This could be very useful if need to check if a library has been installed.
# The function library() will show every package and its version installed in our computer
# However it is too much information
# We can create a vector with the name of the packages to check later if a package is in it
my_packages <- library()$results[,1]
head(my_packages, 10)## [1] "abind" "Amelia" "AnnotationDbi" "antiword"
## [5] "arules" "arulesViz" "assertthat" "audio"
## [9] "automap" "backports"# Now we can check if some package is installed
# We added the tolower function to avoid problems with capital letters
"dplyr" %in% tolower(my_packages)## [1] TRUE# We can list the libraries that are actually loaded doing
(.packages())## [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods"
## [7] "base"# We can check that it actually works
library(ggplot2)
(.packages())## [1] "ggplot2" "stats" "graphics" "grDevices" "utils" "datasets"
## [7] "methods" "base"# Again we could check if a library is loaded
"dplyr" %in% tolower((.packages()))## [1] FALSE# And load it if it's not loaded yet
if(! "dplyr" %in% tolower((.packages()))){
library("dplyr")
(.packages())
}##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## [1] "dplyr" "ggplot2" "stats" "graphics" "grDevices" "utils"
## [7] "datasets" "methods" "base"# We could use the require function for the same purpose
require("readr")## Loading required package: readr(.packages())## [1] "readr" "dplyr" "ggplot2" "stats" "graphics"
## [6] "grDevices" "utils" "datasets" "methods" "base"In this tutorial we have learnt how to list all the installed libraries in R as well as how to find if certain library has been loaded.