![]() ![]() After this, when you open up your R environment, the package should be gone and you will find that you do not have access to it any longer. If you have this problem, you should shut down the R environment and then manually delete the package before starting up your R environment again. However, the computer may not let you do this while the R environment is still running. The best solution for this issue is to manually delete the package. Sometimes a package does not uninstall when you run the command. ![]() If you do, you may want to consider removing them along with it. The way to avoid this problem is to go over your R programs to see if you still have any that use the package you are considering uninstalling. This would be an easy problem to encounter because you could forget that you uninstalled the package or forget that that particular program uses the package that you just deleted. These error messages will include a function not found error. If you have any programs that were using that package and you try to run them, you will get error messages. This would be the most common issue you are likely to have after uninstalling a package. In this case, we tried connecting a package to our program that we had uninstalled. ![]() If you try to access the package after uninstalling it, you will get an error message as seen in this example where we tried to uninstall a package that we have just uninstalled.Įrror in library(dplyr) : there is no package called ‘dplyr’ There are some common issues that can arise when you uninstall a previously installed package.Įrror in remove.packages : there is no package called ‘dplyr’ It is important to make sure that you have any packages installed that you need to run a given program before you run it. ![]() When removing a package removing the code that uses it will help you to avoid getting errors from trying to run nonexistent functions. Because uninstalling a package makes it unusable you need to make sure that you remove any code that uses it. If you are not careful when uninstalling a package, you could find yourself having to deal with error messages if you try to run a program that you used that package in. The package removal process will render the functions defined by the package nonfunctional. The remove packages function usually works quickly and easily. The main reason it often takes longer to install a package than it does to uninstall it is the fact that uninstalling a package does not require the time or process involved in downloading the package and unpacking it for installation. In fact, it often takes less time than it does to originally install the package. If you want to use the functions again you will have to reinstall the package.Īs you can see from the above example, uninstalling a package does not take long. If you load a program that you had previously written using the functions from a package that you have uninstalled you will get error messages. Once you have applied this function to a package that you had previously installed it will no longer be available for use. This simple function easily uninstalls the selected package. Removing package from ‘C:/Users/ccrea/Documents/R/win-library/3.6’ Because of this, you must add it using the library function with the format of library(name), where “name” is the name of the package being loaded. These dependencies occur because you can always use functions from one package to create new functions to be included with another in a new package.Īfter you have installed the package, it is not automatically included in your program. This ensures that the package you are installing will be fully functional as soon as you have installed it. When you install a package in R, you get more than just that package but any packages that it has a dependency with as well. You can think of an R package as a toolbox that you can add to your R programs to be able to process data in ways not available, or difficult to do using the functions that come with the R programming language. Sometimes those datasets will have information that can be used for other purposes. Datasets are often provided as part of these collections to supply test data as you learn to use the functions in the package. What are packages and how do they work in the R environmentĪn R package is a prepackaged collection of functions and datasets that helped supply more functionality to the R programming language. ![]()
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