The {portion} R package offers convenient tools to extract data portions from various objects:
works for vector, matrix, data.frame, and list objects
the relative portion size can be selected
allows to extract first, last, random, similar or dissimilar data
can portion row- and column-wise
provides selected indices as an attribute
preserves object attributes
You can install the released version from CRAN with:
install.packages("portion")
Can portion a vector:
x <- c(1, 1, 2, 2) portion(x, proportion = 0.5, how = "similar") #> [1] 1 1 #> attr(,"indices") #> [1] 1 2 portion(x, proportion = 0.5, how = "dissimilar") #> [1] 1 2 #> attr(,"indices") #> [1] 1 3
Can portion a matrix:
x <- matrix(LETTERS[1:24], nrow = 4) portion(x, proportion = 0.5, how = "first") #> [,1] [,2] [,3] [,4] [,5] [,6] #> [1,] "A" "E" "I" "M" "Q" "U" #> [2,] "B" "F" "J" "N" "R" "V" #> attr(,"indices") #> [1] 1 2 portion(x, proportion = 0.5, how = "first", byrow = FALSE) #> [,1] [,2] [,3] #> [1,] "A" "E" "I" #> [2,] "B" "F" "J" #> [3,] "C" "G" "K" #> [4,] "D" "H" "L" #> attr(,"indices") #> [1] 1 2 3
Can portion a data.frame:
x <- as.data.frame(diag(8)) portion(x, proportion = 0.3, how = "random") #> V1 V2 V3 V4 V5 V6 V7 V8 #> 1 1 0 0 0 0 0 0 0 #> 3 0 0 1 0 0 0 0 0 #> 7 0 0 0 0 0 0 1 0 portion(x, proportion = 0.3, how = "random", byrow = FALSE) #> V1 V2 V5 #> 1 1 0 0 #> 2 0 1 0 #> 3 0 0 0 #> 4 0 0 0 #> 5 0 0 1 #> 6 0 0 0 #> 7 0 0 0 #> 8 0 0 0
Can work on a list:
x <- list(1:5, diag(3), data.frame(1:3, 2:4)) portion(x, proportion = 0.5, how = "last") #> [[1]] #> [1] 3 4 5 #> attr(,"indices") #> [1] 3 4 5 #> #> [[2]] #> [,1] [,2] [,3] #> [1,] 0 1 0 #> [2,] 0 0 1 #> attr(,"indices") #> [1] 2 3 #> #> [[3]] #> X1.3 X2.4 #> 2 2 3 #> 3 3 4
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