Exclude specific value from unique value count
I'm trying to count how many different answers a person gives during a test experiment, but there is a catch.
It is assumed that there are 6 possible answers (1,2,3,4,5,6), but sometimes 0 is written as an answer (this is a glitch / defect in design).
I need to count the number of different answers they give BUT ONLY counting unique values in the range 1-6. This helps us calculate their accuracy.
Is there a way to exclude the value 0 from the contribution to the unique count of values? Any other workarounds?
I am currently trying this method below, but it includes 0, NA and I think any other entry in the cell in the unique count column (I named "Span6"), which makes me sad.
# My Span6 calculator:
ASixImageTrials <- data.frame(eSOPT_831$T8.RESP, eSOPT_831$T9.RESP, eSOPT_831$T10.RESP, eSOPT_831$T11.RESP, eSOPT_831$T12.RESP, eSOPT_831$T13.RESP)
ASixImageTrials$Span6 = apply(ASixImageTrials, 1, function(x) length(unique(x)))
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Use na.omit
inside unique and sum boolean vector like below
df$res = apply(df, 1, function(x) sum(unique(na.omit(x)) > 0))
df
Output:
X1 X2 X3 X4 X5 res
1 2 1 1 2 1 2
2 3 0 1 1 2 3
3 3 NA 1 1 3 2
4 3 3 3 4 NA 2
5 1 1 0 NA 3 2
6 3 NA NA 1 1 2
7 2 0 2 3 0 2
8 0 2 2 2 1 2
9 3 2 3 0 NA 2
10 0 2 3 2 2 2
11 2 2 1 2 1 2
12 0 2 2 2 NA 1
13 0 1 4 3 2 4
14 2 2 1 1 NA 2
15 3 NA 2 2 NA 2
16 2 2 NA 3 NA 2
17 2 3 2 2 2 2
18 2 NA 3 2 2 2
19 NA 4 5 1 3 4
20 3 1 2 1 NA 3
Data:
set.seed(752)
mat <- matrix(rbinom(100, 10, .2), nrow = 20)
mat[sample(1:100, 15)] = NA
data.frame(mat) -> df
df$res = apply(df, 1, function(x) sum(unique(na.omit(x)) > 0))
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Could you please change your question and find out why this doesn't solve your problem?
# here is a numeric vector with a bunch of numbers
mtcars$carb
# here is how to limit that vector to only 1-6
mtcars$carb[ mtcars$carb %in% 1:6 ]
# here is how to tabulate that result
table( mtcars$carb[ mtcars$carb %in% 1:6 ] )
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