David:
I cannot demonstrate _with_ _code_ , otherwise I would not have a
problem. However, I can illustrate:
In SAS, I can run Proc SQL for a dump, VARLIST_IS_HERE, showing on the
computer screen the variables, e.g., ID, X1, X2, X3, ..., X1000,
that I can copy and paste into the editor window (e.g., R Source
window) to easily select which variables among the big data of today
I want keep.
David Winsemius wrote:
It would be best if you could demonstrate _with_ _code_ the sort of operation
you propose.
David
Sent from my iPhone
On Apr 23, 2017, at 1:07 PM, Bruce Ratner PhD <b...@dmstat1.com> wrote:
R-helpers:
I'm reading "Advanced R" (Wickham), which provides his way, quoted below, of
keeping variables. This cherry-picking approach clearly is not practical with a large
dataset.
"If you know the columns you don’t want, use set operations to work out which colums to keep:
df[setdiff(names(df), "z")]"
I'm looking for a way of producing an output of 1000 plus variables, such that
I can get a clean listing of variables, not like from st(), that are easily
copy-pastable for selecting the variables I want to keep.
Any suggestion is appreciated.
Thanks.
Bruce
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