This recipe demonstrates the two different ways to load a package after installation.Īccess Loan Eligibility Prediction Projects with Source Code Step 1: Installing packages It is very crucial to load the package before using it in code. We can all the default packages by using code : 'library()'.

There already exists some default packages in the local directory 'library' on your machine when you install R. For Example, 'dplyr' is one of the commonly used packages in R which adds further functionalities with respect to working with dataframes. They are stored in the 'library' directory in the R-environment and developed by the community. Because the examples are live tests which are executed automatically by the check command, they must be real and compact.R packages consists of a collection of R functions, data sets and compiled code which adds value to the existing R-functionalities. The Rd format is described at the following page.

Mainly, the help files in man folder are required to be updated. Editing some of them are required before going to the build step. These files are almost done, but not completed. package.skeleton() package.skeleton(name='HelloWorld', list=c('hello.world'))Ī HelloWorld folder is created at the R temporary folder, and the package files are put in it. hello.world <-įunction(to.whom='world') cat('Hello,', to.whom, fill=T)Ģ.

The package name is HelloWorld, and that contains only a function hello.world().ġ. Let’s make a traditional Hello World package. check the package using the R CMD check command.build a package using the R CMD build command.create a new package using the package.skeleton() function.Now, I am trying to make my first R package. So making a package from a matured R script is a good way, which will improve the ease of use. A package can be managed as library at local disk or repository such as CRAN. Or I can load a package file using library() function.Ī benefit of using a package is the easy management. I can read a source file using source() function. I can write a code and run it on the fly by the terminal.

Making a package in r