问题:

A data.table novice question. I would like to transform a set of columns in a data.table by applying a mathematical formula to them. The set of columns must exclude 1 or more of the total number of columns.

In data.frame terms I would do:

data(iris) head(iris)   Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1          5.1         3.5          1.4         0.2  setosa 2          4.9         3.0          1.4         0.2  setosa 3          4.7         3.2          1.3         0.2  setosa 4          4.6         3.1          1.5         0.2  setosa 5          5.0         3.6          1.4         0.2  setosa 6          5.4         3.9          1.7         0.4  setosa  iris[, -5] <- iris[, -5] * 1e3 head(iris)   Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1         5100        3500         1400         200  setosa 2         4900        3000         1400         200  setosa 3         4700        3200         1300         200  setosa 4         4600        3100         1500         200  setosa 5         5000        3600         1400         200  setosa 6         5400        3900         1700         400  setosa

I know how to select multiple columns in a data.table:

iris.dt <- data.table(iris) head(iris.dt[, -5, with = FALSE])

or even:

head(iris.dt[, !"Species", with = FALSE])

How to actually transform those selected columns taking advantage of data.table pass-by-reference?

回答1:

What about using the .SDCols argument along with assignment by reference (:=):

DT <- data.table(iris) DT[, c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")    :=lapply(.SD, function(x) x*1000), .SDcols=1:4] # Alternatively you can grab the names the usual way: # DT[, names(DT)[1:4] := lapply(.SD, function(x) x*1000), .SDcols=1:4] DT #      Sepal.Length Sepal.Width Petal.Length Petal.Width   Species #   1:         5100        3500         1400         200    setosa #   2:         4900        3000         1400         200    setosa #   3:         4700        3200         1300         200    setosa #   4:         4600        3100         1500         200    setosa #   5:         5000        3600         1400         200    setosa #  ---                                                             # 146:         6700        3000         5200        2300 virginica # 147:         6300        2500         5000        1900 virginica # 148:         6500        3000         5200        2000 virginica # 149:         6200        3400         5400        2300 virginica # 150:         5900        3000         5100        1800 virginica

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transform

iris