During the course of statistical analysis and machine learning, R programming provides the application of saving and loading data for the purpose of utilizing it again when needed. Utilizing this feature is essential in making your analysis process efficient by saving time and computational resources. It enables swift handling of data, preventing the need for running scripts or complex calculations everytime. RData is the file format used to store R objects in binary form which can be loaded back to R when required. This article will deliberate on the process of saving and loading data using RData in R programming step by step explanation of the segment of code we’ll use to do so.
Saving as RData
The first step involves saving your work into an RData file. This is achieved by the use of the save() function in R. The basic syntax to save one or more R objects in an RData file is as follows:
# Saving R objects. save(object1, object2, ..., file = "your_file.RData")
In the above syntax, ‘object1, object2, …’ represent the R objects that you want to save, and ‘your_file.RData’ is the name of the file where these objects will be saved. If no file path is provided, the file will be saved in the current working directory.
Loading RData
After your work has been saved in an RData file, the next step would be to load it back into R when required. The function to load an RData file in R is load(). The following R code demonstrates how to load an RData file:
# Loading RData file.
load("your_file.RData")
This command loads the R objects saved in ‘your_file.RData’ into the current R workspace. After this, you should be able to call and use your previously saved R objects directly in your R environment.
Use of Libraries in Saving and Loading R Data
R is known for its packages or libraries that feature tools to simplify and perform complex tasks. Saving and loading data is no different. In addition to the main R functions save() and load(), other libraries such as ”rio” and ”R.utils” can be be used in saving and loading data in R.
- The library ”rio” has a function called export that can be used to save R objects.
- The library ”R.utils” has a function called saveRDS that saves R objects in binary format, and the function loadRDS to load them back to R environment.
Both these libraries provide alternatives to save and load R data and are worth exploring in different use cases.
