R equivalent to matrix row insertion in Matlab

0
votes

In Matlab, without any coding, I can create a matrix, open up its spreadsheet, and copy multiple columns of values from Excel and paste them into the spreadsheet. I can then right click this matrix and plot it instantly.

I've tried googling for how to do the equivalent in R, and everything seems to involve creating a function iterating over each value with a for loop. This seems a bit cumbersome, is there an equivalent simple way to do this in RStudio?

Thanks.

1
rmatlab
I'm pretty certain the answer is no. There is fix(), which will give you an editable spreadsheet-type object, but I don't think it will let you copy / past whole columns. There also isn't a point-click type interface; there is Rcommander, though. – gung - Reinstate Monica

1 Answers

0
votes

You certainly can have a similar functionality by using R's integration with a clipboard. In particular, standard R functions that provide support for clipboard operations include connection functions (base package), such as file(), url(), pipe() and others, clipboard text transfer functions (utils package), such as readClipboard(), writeClipboard(), as well as data import functions (base package), which use connection argument, such as scan() or read.table().

This functionality differs from platform to platform. In particular, for Windows platform, you need to use connection name clipboard, for Mac platform (OS X) - you can use pipe("pbpaste") (see this StackOverflow discussion for more details and alternative methods). It appears that Kmisc package offers a platform-independent approach to that functionality, however, I haven't used it so far, so, can't really confirm that it works as expected. See this discussion for details.

The following code is a simplest example of how you would use the above-mentioned functionality:

read.table("clipboard", sep="\t", header=header, ...)

An explanation and further examples are available in this blog post. As far as plotting the imported data goes, RStudio not only allows you to use standard R approaches, but also adds an element of interactivity via its bundled manipulate package. See this post for more details and examples.