Tutorial :What useful R package doesn't currently exist? [closed]


I have been working on a few R packages for some general tools that aren't currently available in R: blogging, report delivery, logging, and scheduling. This led me to wonder: what are the most important things that people wish existed in R that currently aren't available?

My hope is that we can use this to pinpoint some gaps, and possibly work on them collaboratively.


I'm a former Mathematica junkie, and one thing that I really miss is the notebook style interface. When I did my research with notebooks, papers would almost write themselves as I did my analysis. But now that I'm using R, I find that documenting my work to be quite tedious.

For people that are not so familiar with Mathematica, you have documents called "notebooks" that can contain code, text, equations, and the results from executed code (which can be equations, text, graphics, or interactive tools). Everything can be neatly organized into styled subsections or sections that are collapsable. You can have multiple open documents that integrate with a single shared kernel.

While I don't think a full-blown Mathematica style interface is entirely necessary, some interactive document system that would support text (for description), code, code output, and embedded image output would be a real boon to researchers.


A Real-Time R package would be my choice, using C Streaming perhaps.

Also I'd like a more robust web development package. Nothing as extensive as Ruby on Rails but something a bit better than Sweave combined with R2HTML, that can run on RApache. I think this needs to be a huge area of emphasis for R in general.

I realize LaTeX is better markup for certain academia but in general I think HTML should be the markup language of choice. More needs to be done in terms of R Web Apps, so applications can be hosted on huge RAM remotely and R can start being used for SaaS data applications and other graphics choices.


Interfaces to any of the new-fangled 'Web 2.0' databases that use key-value pairs rather than the standard RDMS. A non-exhaustive list (in alphabetical order) would be

and it would of course be nice if we had a DBI-alike abstraction on top of this. Jeff has started with RBerkeley but that use the older-school Oracle BerkeleyDB backend rather than one of those new things.


An output device which produces Javascript code, perhaps using the protovis library.


as a programmer and writer of libraries for colleagues, I was definitely missing a logging package, I googled and asked around, here too, then wrote one myself. it is on r-forge, here, and it s called "logging" :)

I use it and I'm obviously still developing it.


There are few libraries to interface with database in general, and there is not ORM library.

RMySQL is useful, but you have to write the SQL queries manually and there is not a way to generate them as in a ORM. Morevoer, it is only specific to MySQL.

Another library set that R still doesn't have, for me, it is a good system for reading command line arguments: there is R getopt but it is nothing like, for example, argparse in python.


A natural interface to the .NET framework would be awesome, though I suspect that that might be a lot of work.

EDIT: Syntax highlighting from within RGui would also be wonderful.

ANOTHER EDIT: R.NET now exists to integrate R with .NET.


A FRAQ package for FRequently Asked Questions, a la fortune(). R-help would be so much fun: "Try this, library(FRAQ); faq("lattice won't print"), etc.

See also.


A wiki package that adds wiki-like documentation to R packages. You'd have a inst/wiki subdirectory with plain text files in markdown, asciidoc, textile, with embedded R code. With the right incantation, these files would be executed (think brew and/or asciidoc packages), and the relevant output uploaded to a given repository online (github, googlecode, etc.). Another function could take care of synchronizing the changes made online, typically via svn or git.

Suddenly you have a wiki documentation for your package with reproducible examples (could even be hooked to R CMD check).

EDIT 2012:

... and now the knitr package would make this process even easier and neater


I would like to see a possibility to embed another programming language within R in a more straightforward way by the users. I give this as an example in some common-lisp implementations one could write a function with embedded C code like this:

(defun sample (x)    (ffi:c-inline (n1 n2) (:int :int) (values :int :int) "{      int n1 = #0, n2 = #1, out1 = 0, out2 = 1;      while (n1 <= n2) {        out1 += n1;        out2 *= n1;        n1++;      }      @(return 0)= out1;      @(return 1)= out2;      }"     :side-effects nil))  

It would be good if one could write an R function with embedded C or lisp code (more interested in the latter) in a similar way.


A native .NET interface to RGUI. R(D)Com is based on COM, and it only allows to exchange matrices, not more complex structures.


I would very much like a line profiler. This exists in Matlab and Python, and is very useful for finding bits of code that take a lot of time or are executed more (or less) than expected. A lot of my code involves function optimizations and how many times something iterates may not be known in advance (though most iterations are constrained or specified).

The call stack is useful if all of your code is in R and is very simple, but as I recently posted about it, it takes a painstaking effort if your code is complex.

It's quite easy to develop a line profiler for a given bit of code. A naive way is to index every line (or just pre-specified sections) and insert a call to log proc.time() that line. In a loop, I simply enumerate sections of code and store in a 2 dimensional list the proc.time values for section i in iteration k. [See update below: this isn't actually a way to do a line profiler for all kinds of code.]

One can use such a tool to find hotspots, anomalies (e.g. code that should be O(n) but is really O(n^2)), code that may benefit from memoization (a line profiler doesn't tell you this, but it lets you know where to look), code that is mistakenly inside a loop, and more.

Update 1: Inserting a timing line between every function line is slightly erroneous: the definition of a line of code is not simply code separated by whitespace. Being able to parse the code into an AST is necessary for knowing where operations begin and end. As discussed in some of the answers to this question, there are some tools (namely, showTree and walkCode in the codetools package) for doing this. Simply applying a regular expression to source code would be a very bad thing to do.

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