The post is about an introduction to workspace, R objects, and .Rdata file in R language.
Table of Contents
R Language as Functional Language
The R program’s structure is similar to the programs written in other computer languages such as C or its successors C++ and Java. However, important differences between these languages and R are (i) R has no header files, (ii) most of the declarations are implicit, (iii) there are no pointers in R, and (iv) text and strings as vectors can be defined and manipulated directly.
R is a functional language. Most of the computation in R is handled using functions. The R language environment is designed to facilitate the development of new scientific computation tools.
R Objects
Everything (such as functions and data structure) in R is an object. To see the names of all R objects in the workspace, on the R command prompt just type,
ls()
objects() is an alternative to ls() function. Similarly, typing the name of any object on the R prompt displays (prints) the content of that object. As an example type q, mean, and lm, etc. on the R prompt.
R Workspace
It is possible to save individual objects or collections of objects into a named image file. The named image file has an extension of .RData. Some possibilities to save an object from R workspace are:
To save the content of R workspace into a file .RData, type
save.image()
To save objects in the file archive.RData, type
save.image(file = "archive.RData")
To save some required objects in data.RData, type
save(x, y, file = "data.RData")
These image files can be attached to make objects available in the next R session. For example.
attached ("arvhive.RData")
Note that when quitting, R offers the option of saving the workspace image. By default, the workspace is saved in an image file (.RData) in the working directory. The image file can be used in the next R session. Saving the workspace image will save everything from the current workspace. Therefore, use the rm() function to remove objects that are not further required in the next R session.
For further details about saving and loading R workspace visit: Save and Load R Workspace
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