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R Tip: Give data.table a Try

If your R or dplyr work is taking what you consider to be a too long (seconds instead of instant, or minutes instead of seconds, or hours instead of minutes, or a day instead of an hour) then try data.table. For some tasks data.table is routinely faster than alternatives at […]

Speed up your R Work

Introduction In this note we will show how to speed up work in R by partitioning data and process-level parallelization. We will show the technique with three different R packages: rqdatatable, data.table, and dplyr. The methods shown will also work with base-R and other packages. For each of the above […]

R Tip: Be Wary of “…”

R Tip: be wary of “…“. The following code example contains an easy error in using the R function unique(). vec1 <- c("a", "b", "c") vec2 <- c("c", "d") unique(vec1, vec2) # [1] "a" "b" "c" Notice none of the novel values from vec2 are present in the result. Our […]

R Tip: use isTRUE()

R Tip: use isTRUE(). A lot of R functions are type unstable, which means they return different types or classes depending on details of their values. For example consider all.equal(), it returns the logical value TRUE when the items being compared are equal: all.equal(1:3, c(1, 2, 3)) # [1] TRUE […]