Adam - 1 month ago 7x
R Question

# Count number of columns by a condition (>) for each row

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.

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))
``````