[R] Why does R replace all row values with NAs

William Dunlap wdunlap at tibco.com
Fri Feb 27 17:04:36 CET 2015


You could define functions like
   is.true <- function(x) !is.na(x) & x
   is.false <- function(x) !is.na(x) & !x
and use them in your selections.  E.g.,
  > x <- data.frame(a=1:10,b=2:11,c=c(1,NA,3,NA,5,NA,7,NA,NA,10))
  > x[is.true(x$c >= 6), ]
      a  b  c
  7   7  8  7
  10 10 11 10


Bill Dunlap
TIBCO Software
wdunlap tibco.com

On Fri, Feb 27, 2015 at 7:27 AM, Dimitri Liakhovitski <
dimitri.liakhovitski at gmail.com> wrote:

> Thank you very much, Duncan.
> All this being said:
>
> What would you say is the most elegant and most safe way to solve such
> a seemingly simple task?
>
> Thank you!
>
> On Fri, Feb 27, 2015 at 10:02 AM, Duncan Murdoch
> <murdoch.duncan at gmail.com> wrote:
> > On 27/02/2015 9:49 AM, Dimitri Liakhovitski wrote:
> >> So, Duncan, do I understand you correctly:
> >>
> >> When I use x$x<6, R doesn't know if it's TRUE or FALSE, so it returns
> >> a logical value of NA.
> >
> > Yes, when x$x is NA.  (Though I think you meant x$c.)
> >
> >> When this logical value is applied to a row, the R says: hell, I don't
> >> know if I should keep it or not, so, just in case, I am going to keep
> >> it, but I'll replace all the values in this row with NAs?
> >
> > Yes.  Indexing with a logical NA is probably a mistake, and this is one
> > way to signal it without actually triggering a warning or error.
> >
> > BTW, I should have mentioned that the example where you indexed using
> > -which(x$c>=6) is a bad idea:  if none of the entries were 6 or more,
> > this would be indexing with an empty vector, and you'd get nothing, not
> > everything.
> >
> > Duncan Murdoch
> >
> >
> >>
> >> On Fri, Feb 27, 2015 at 9:13 AM, Duncan Murdoch
> >> <murdoch.duncan at gmail.com> wrote:
> >>> On 27/02/2015 9:04 AM, Dimitri Liakhovitski wrote:
> >>>> I know how to get the output I need, but I would benefit from an
> >>>> explanation why R behaves the way it does.
> >>>>
> >>>> # I have a data frame x:
> >>>> x = data.frame(a=1:10,b=2:11,c=c(1,NA,3,NA,5,NA,7,NA,NA,10))
> >>>> x
> >>>> # I want to toss rows in x that contain values >=6. But I don't want
> >>>> to toss my NAs there.
> >>>>
> >>>> subset(x,c<6) # Works correctly, but removes NAs in c, understand why
> >>>> x[which(x$c<6),] # Works correctly, but removes NAs in c, understand
> why
> >>>> x[-which(x$c>=6),] # output I need
> >>>>
> >>>> # Here is my question: why does the following line replace the values
> >>>> of all rows that contain an NA # in x$c with NAs?
> >>>>
> >>>> x[x$c<6,]  # Leaves rows with c=NA, but makes the whole row an NA.
> Why???
> >>>> x[(x$c<6) | is.na(x$c),] # output I need - I have to be
> super-explicit
> >>>>
> >>>> Thank you very much!
> >>>
> >>> Most of your examples (except the ones using which()) are doing logical
> >>> indexing.  In logical indexing, TRUE keeps a line, FALSE drops the
> line,
> >>> and NA returns NA.  Since "x$c < 6" is NA if x$c is NA, you get the
> >>> third kind of indexing.
> >>>
> >>> Your last example works because in the cases where x$c is NA, it
> >>> evaluates NA | TRUE, and that evaluates to TRUE.  In the cases where
> x$c
> >>> is not NA, you get x$c < 6 | FALSE, and that's the same as x$c < 6,
> >>> which will be either TRUE or FALSE.
> >>>
> >>> Duncan Murdoch
> >>>
> >>
> >>
> >>
> >
>
>
>
> --
> Dimitri Liakhovitski
>
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