By adamleerich
Unless you have configured R not to ask, every time you close R or RStudio you are prompted to save your workspace. This saves an RData file to the working directory. The functions save.image() and save() offer a little more flexibility, but basically do the same thing: they save all or part of your current workspace to disk.
Let’s say last week I did some analysis on the built-in dataset called iris and I executed the following right before ending my R session
> ls()
[1] 'fit1' 'iris' 'species'
> save.image('MyData.RData')
This saved the three objects in my global environment to a file called MyData.
Now I am ready to do a similar analysis on another data set about daisies. I load up the daisies data frame and create a unique list of all the species.
> ls() [1] 'daisies' 'species'
I want to experiement with some models but I first want to take a look at what I did in the iris study, for reference. I load up the MyData file from the iris analysis using the following
> load('MyData.RData')
> ls()
[1] 'daisies' 'fit1' 'iris' 'species'
The problem with the default behavior of load() is that it does not allow me to load just one of the objects from the file but requires me to load all and throws them in my global environment. Sometimes, like here, this writes over objects that already exist in memory. My daisy species object got overwritten by the iris species object I had saved to disk.
This isn’t really a problem if you always give objects unique names or if you remember every object you have saved in every file, but really, who can possibly do that? There is another way to combat this and that is to not rely on load()‘s default behavior. The second parameter allows …read more
Source:: r-bloggers.com