I have a table of (x,y) points and would like to create a second table that summarizes those points.
I would like each row in the summary table to show the sum of all the y's where x is greater than a sequence of thresholds. But I'm having trouble figuring out how to join the threshold value of the row into the inner sum.
I've gotten this far:
samples <- data.table(x=seq(1,100,1), y=seq(1,100,1))
thresholds = seq(10,100,10)
thresholdedSums <- data.table(xThreshold=thresholds, ySumWhereXGreaterThanThreshold=sum(samples[x > xThreshold, y]))
Error in eval(expr, envir, enclos) : object 'xThreshold' not found
How would I accomplish this, or is there a different way to do this sort of thing?
To clarify desired output:
thresholdedSums =
[
(row 1) threshold = 10, ySumWhereXGreaterThanThreshold = sum of all y values in samples[] where x > 10,
(row 2) threshold = 20, ySumWhereXGreaterThanThreshold = sum of all y values in samples[] where x > 20,
... etc ...
]
The result can be given by the following code. This solution is not completely based on data.table but works robustly.
thresholdedSums <- data.table(
thres = thresholds,
Sum = sapply(thresholds, function(thres) samples[x > thres, sum(y)])
)
# thres Sum
# 1: 10 4995
# 2: 20 4840
# 3: 30 4585
# 4: 40 4230
# 5: 50 3775
# 6: 60 3220
# 7: 70 2565
# 8: 80 1810
# 9: 90 955
# 10: 100 0
Additional explanation: sapply(thresholds, function(thres) samples[x > thres, sum(y)]) returns a vector of the same length as thresholds. You can read it as: For every element in thresholds execute the function function(thres) samples[x > thres, sum(y)] and return the result as a vector. In comparison to a for-loop this procedure is normally better in performance and easier to read.
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