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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
You can install the released version from CRAN with:
install.packages("portion")
Can portion a vector
:
<- c(1:4, 16:20)
x portion(x, proportion = 0.5, how = "similar")
#> [1] 16 17 18 19 20
#> attr(,"indices")
#> [1] 5 6 7 8 9
portion(x, proportion = 0.4, how = "dissimilar")
#> [1] 1 2 16 17
#> attr(,"indices")
#> [1] 1 2 5 6
Can portion a matrix
:
<- matrix(LETTERS[1:24], nrow = 4)
x 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
:
<- as.data.frame(diag(8))
x 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
#> 4 0 0 0 1 0 0 0 0
portion(x, proportion = 0.3, how = "random", byrow = FALSE)
#> V3 V4 V8
#> 1 0 0 0
#> 2 0 0 0
#> 3 1 0 0
#> 4 0 1 0
#> 5 0 0 0
#> 6 0 0 0
#> 7 0 0 0
#> 8 0 0 1
Can work on a list
:
<- list(1:5, diag(3), data.frame(1:3, 2:4))
x 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
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.