If I want to select a subset of data in R, I can use the subset f开发者_如何学JAVAunction. I wanted to base an analysis on data that that was matching one of a few criteria, e.g. that a certain variable was either 1, 2 or 3. I tried
myNewDataFrame <- subset(bigfive, subset = (bigfive$bf11==(1||2||3)))
It did always just select values that matched the first of the criteria, here 1. My assumption was that it would start with 1 and if it does evaluate to "false" it would go on to 2 and than to 3, and if none matches the statement after == is "false" and if one of them matches, it is "true".
I got the right result using
newDataFrame <- subset(bigfive, subset = (bigfive$bf11==c(1,2,3)))
But I would like to be able to select data via logical operators, so: why did the first approach not work?
The correct operator is %in%
here. Here is an example with dummy data:
set.seed(1)
dat <- data.frame(bf11 = sample(4, 10, replace = TRUE),
foo = runif(10))
giving:
> head(dat)
bf11 foo
1 2 0.2059746
2 2 0.1765568
3 3 0.6870228
4 4 0.3841037
5 1 0.7698414
6 4 0.4976992
The subset of dat
where bf11
equals any of the set 1,2,3
is taken as follows using %in%
:
> subset(dat, subset = bf11 %in% c(1,2,3))
bf11 foo
1 2 0.2059746
2 2 0.1765568
3 3 0.6870228
5 1 0.7698414
8 3 0.9919061
9 3 0.3800352
10 1 0.7774452
As to why your original didn't work, break it down to see the problem. Look at what 1||2||3
evaluates to:
> 1 || 2 || 3
[1] TRUE
and you'd get the same using |
instead. As a result, the subset()
call would only return rows where bf11
was TRUE
(or something that evaluated to TRUE
).
What you could have written would have been something like:
subset(dat, subset = bf11 == 1 | bf11 == 2 | bf11 == 3)
Which gives the same result as my earlier subset()
call. The point is that you need a series of single comparisons, not a comparison of a series of options. But as you can see, %in%
is far more useful and less verbose in such circumstances. Notice also that I have to use |
as I want to compare each element of bf11
against 1
, 2
, and 3
, in turn. Compare:
> with(dat, bf11 == 1 || bf11 == 2)
[1] TRUE
> with(dat, bf11 == 1 | bf11 == 2)
[1] TRUE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE
For your example, I believe the following should work:
myNewDataFrame <- subset(bigfive, subset = bf11 == 1 | bf11 == 2 | bf11 == 3)
See the examples in ?subset
for more. Just to demonstrate, a more complicated logical subset would be:
data(airquality)
dat <- subset(airquality, subset = (Temp > 80 & Month > 5) | Ozone < 40)
And as Chase points out, %in%
would be more efficient in your example:
myNewDataFrame <- subset(bigfive, subset = bf11 %in% c(1, 2, 3))
As Chase also points out, make sure you understand the difference between |
and ||
. To see help pages for operators, use ?'||'
, where the operator is quoted.
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