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R packages are a collection of R functions, complied code and sample data. They are stored under a directory called **"library"** in the R environment. By default, R installs a set of packages during installation. More packages are added later, when they are needed for some specific purpose. When we start the R console, only the default packages are available by default. Other packages which are already installed have to be loaded explicitly to be used by the R program that is going to use them.

All the packages available in R language are listed at R Packages.

Below is a list of commands to be used to check, verify and use the R packages.

Get library locations containing R packages

.libPaths()

When we execute the above code, it produces the following result. It may vary depending on the local settings of your pc.

[2] "C:/Program Files/R/R-3.2.2/library"

library()

When we execute the above code, it produces the following result. It may vary depending on the local settings of your pc.

Packages in library ‘C:/Program Files/R/R-3.2.2/library’: base The R Base Package boot Bootstrap Functions (Originally by Angelo Canty for S) class Functions for Classification cluster "Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al. codetools Code Analysis Tools for R compiler The R Compiler Package datasets The R Datasets Package foreign Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ... graphics The R Graphics Package grDevices The R Graphics Devices and Support for Colours and Fonts grid The Grid Graphics Package KernSmooth Functions for Kernel Smoothing Supporting Wand & Jones (1995) lattice Trellis Graphics for R MASS Support Functions and Datasets for Venables and Ripley's MASS Matrix Sparse and Dense Matrix Classes and Methods methods Formal Methods and Classes mgcv Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness Estimation nlme Linear and Nonlinear Mixed Effects Models nnet Feed-Forward Neural Networks and Multinomial Log-Linear Models parallel Support for Parallel computation in R rpart Recursive Partitioning and Regression Trees spatial Functions for Kriging and Point Pattern Analysis splines Regression Spline Functions and Classes stats The R Stats Package stats4 Statistical Functions using S4 Classes survival Survival Analysis tcltk Tcl/Tk Interface tools Tools for Package Development utils The R Utils Package

Get all packages currently loaded in the R environment

search()

When we execute the above code, it produces the following result. It may vary depending on the local settings of your pc.

[1] ".GlobalEnv" "package:stats" "package:graphics" [4] "package:grDevices" "package:utils" "package:datasets" [7] "package:methods" "Autoloads" "package:base"

There are two ways to add new R packages. One is installing directly from the CRAN directory and another is downloading the package to your local system and installing it manually.

The following command gets the packages directly from CRAN webpage and installs the package in the R environment. You may be prompted to choose a nearest mirror. Choose the one appropriate to your location.

install.packages("Package Name") # Install the package named "XML". install.packages("XML")

Go to the link R Packages to download the package needed. Save the package as a **.zip** file in a suitable location in the local system.

Now you can run the following command to install this package in the R environment.

install.packages(file_name_with_path, repos = NULL, type = "source") # Install the package named "XML" install.packages("E:/XML_3.98-1.3.zip", repos = NULL, type = "source")

Before a package can be used in the code, it must be loaded to the current R environment. You also need to load a package that is already installed previously but not available in the current environment.

A package is loaded using the following command −

library("package Name", lib.loc = "path to library") # Load the package named "XML" install.packages("E:/XML_3.98-1.3.zip", repos = NULL, type = "source")

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