Patrick Burns <pbu...@pburns.seanet.com>
> * What were your biggest misconceptions or
> stumbling blocks to getting up and running
> with R?
I came into R from SAS, with its powerful data step language and very
simplified data types. Most of my work is data manipulation prior to a
variety of univariate statistical calculations. The vector-based nature
of R, and thus the variety of indexing schemes used, was a big conceptual
hurdle.
The often unhelpful attitude of several list respondents, while not unique
to this list, was and continues to be another block to advancement. This
does not occur on the list for SAS, in which asking 'dumb' questions is
generally supported as an inevitable part of learning. Having aggregate()
pointed out to me by one kind soul, hidden amidst the assortment of
by()/apply() functions, became the basis for much success.
I am currently trying to wrap my mind around how missing values are
handled; the defaults are quite different than SAS, and mostly in a good
way. However the handling of NA values in a slicing statements does not
seem quite proper, even if it is addressed in the R documents.
aa <- data.frame('id'=letters[1:5], 'x'=1:5,
stringsAsFactors=FALSE)
aa[aa$x == 3,]$x <- NA
aa[aa$x == '4',] # 2 rows instead of 1.
aa[aa$x %in% '4',] # 1 row as expected.
I am also looking for concise methods for building up dataframes for our
unit tests. While there are several ways to accomplish this, depending on
what is needed, none are elegant though expand.grid() comes close.
next: The R inferno. I *will* understand more than the first few pages.
And all those apply()-ish functions, as I'm already good friends with
aggregate().
> * What documents helped you the most in this
> initial phase?
RSeek.org was and continues to be a big source of help. I've looked at
several texts aimed at beginners, and all provided simple examples that
were useful. The most consistent source of instruction has been to make
up my own small projects that were either fun or slightly relevant to my
job. The ability to make up toy problems, or simplify a complex process
have been unexpectedly important skills. Developing unit tests for
functions, initially seen as an irritant by some, has become an important
tool for honing our advances.
> I especially want to hear from people who are
> lazy and impatient.
And, I hope, incompetent. I've found incompetence to be as professionally
important as hubris. I wouldn't want one without the other.
cur
--
Curt Seeliger, Data Ranger
Raytheon Information Services - Contractor to ORD
seeliger.c...@epa.gov
541/754-4638
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