问题
I am trying to work out for each row of a matrix how many columns have values greater than a specified value. I am sorry that I am asking this simple question but I wasn\'t able to figure it out.
I have extracted maximum temperature values from a raster stack, of multiple years of rasters, for some spatial points I am interested in. The data looks similar to:
data <- cbind(\'1990\' = c(25, 22, 35, 42, 44), \'1991\' = c(23, 28, 33, 40, 45), \'1992\' = c(20, 20, 30, 41, 43))
1990 1991 1992
1 25 23 20
2 22 28 20
3 35 33 30
4 42 40 41
5 44 45 43
I want to end up with the number of years that the temperature was above 30 for each location, eg.:
yr.above
1 0
2 0
3 2
4 3
5 3
I have tried a few things but they didn\'t work and were pretty illogical (e.g. trying length(data[1:length(data), which(blah blah doesn\'t make sense)), or apply(data, 1, length(data) > 30), I know these don\'t make sense but I am a bit stuck.
回答1:
This will give you the vector you are looking for:
rowSums(data > 30)
It will work whether data
is a matrix or a data.frame. Also, it uses vectorized functions, hence is a preferred approach over using apply
which is little more than a (slow) for loop.
If data
is a data.frame, you can add the result as a column by doing:
data$yr.above <- rowSums(data > 30)
or if data
is a matrix:
data <- cbind(data, yr.above = rowSums(data > 30))
You can also create a whole new data.frame:
data.frame(yr.above = rowSums(data > 30))
or a whole new matrix:
cbind(yr.above = rowSums(data > 30))
回答2:
The third argument of apply needs to be a function. Also, you can count logical trues with sum.
apply(data, 1, function(x)sum(x > 30))
回答3:
We can also do with Reduce
and +
(assuming there are no NA elements)
Reduce(`+`, lapply(as.data.frame(data), `>`, 30))
This should be efficient as we are not converting to a matrix
.
来源:https://stackoverflow.com/questions/18862114/count-number-of-columns-by-a-condition-for-each-row