R has a very wide audience, clinical research, astronomy, psychology, and so on and so on. I would consider data analysis work to be three stages: data preparation, statistical analysis, and producing the report. This regards the process of getting the data ready for analysis and reporting, sometimes called "data cleaning" or "data munging" or "data wrangling".
So as regards tools for data preparation, speaking to the highly diverse audience mentioned, here is my question: What do you want? Or are you already quite happy with the range of tools that is currently before you? [BTW, I posed the same question last week to the r-devel list, and was advised that r-help might be a more suitable audience by one of the moderators.] Robert Wilkins [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.