Your objections are quite cogent, but I believe they are misdirected. I'm not at all interested in having my students ignore the existence of NA's and that's precisely why I'm not using the Default package as someone else suggested. But the mere existence of missing values in a data set doesn't make computation of the mean entirely useless -- why else would the na.rm option be available. If a student using my version of mean uses it to find the mean of a variable that has missing values, the function first prints a warning message and only then returns a value. Here's an example > length(x) [1] 101 > mean(x) Warning: x has 3 missing values. [1] 51.69388
My only goal in this project has been to provide them with a somewhat friendlyR version of R. It was not conceived as part of a quest to improve my programming proficiency, but my curiousity can be piqued when I run up against a programming problem. Joel ________________________________ From: Steve Lianoglou [mailto:mailinglist.honey...@gmail.com] Sent: Thu 8/13/2009 5:55 PM To: Pitt, Joel Cc: Erik Iverson; r-help@r-project.org Subject: Re: [R] Coding problem: How can I extract substring of function callwithin the function Hi, On Aug 13, 2009, at 5:30 PM, Pitt, Joel wrote: > Thanks. It's a great solution to part of my problem. It provides the > functionally I want would be no harder for students to use than my > approach. I'm still interested in how to make what I was trying to > do work -- simply to add to my own R programming proficiency. I wasn't going to really chime in, but I couldn't help it given the irony in your last sentence (sorry, I don't mean to sound like an ass). I think trying to help your students with some "bumps on the road" is admirable, but this seems just a bit misdirected. As you say, you are on a quest to add to your R programming proficiency, and will apply this newly founded technique to actively handicap your students' proficiency. I guess you're teaching some intro stat analysis class, and waving over the fact that functions like mean explicitly return NA in the presence of NA's, but this is important to know and recognize when analyzing any real data, because there will surely be NA's "in the wild." Knowing that you should consciously and deliberately deal with/ ignore them from the start might be a good first/early lesson for students to digest. Like I said, I don't mean to sound like an ass, but I think glossing over details of working with data should be avoided. Your other additions, like adding options to plotting/graphing functions, seem less harmful to me. But if you're trampling over some base:: function for something trivial like changing the value of one default parameter to something else, you might as well just get them to learn how to use the ?<function_name> asap as well. -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list 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.
