Tiny helper function to calculate the mean and deviations from the mean, both returned as a list. Works nicely with data.table to calculate a between and within variable.
Arguments
- x
A vector, appropriate for the
meanfunction.- na.rm
A logical, whether to remove missing or not. Defaults to
TRUE.
Examples
## simple example showing what it does
meanDeviations(1:10)
#> [[1]]
#> [1] 5.5
#>
#> [[2]]
#> [1] -4.5 -3.5 -2.5 -1.5 -0.5 0.5 1.5 2.5 3.5 4.5
#>
## example use case, applied to a data.table
library(data.table)
d <- as.data.table(iris)
d[, c("BSepal.Length", "WSepal.Length") := meanDeviations(Sepal.Length),
by = Species]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species BSepal.Length
#> <num> <num> <num> <num> <fctr> <num>
#> 1: 5.1 3.5 1.4 0.2 setosa 5.006
#> 2: 4.9 3.0 1.4 0.2 setosa 5.006
#> 3: 4.7 3.2 1.3 0.2 setosa 5.006
#> 4: 4.6 3.1 1.5 0.2 setosa 5.006
#> 5: 5.0 3.6 1.4 0.2 setosa 5.006
#> ---
#> 146: 6.7 3.0 5.2 2.3 virginica 6.588
#> 147: 6.3 2.5 5.0 1.9 virginica 6.588
#> 148: 6.5 3.0 5.2 2.0 virginica 6.588
#> 149: 6.2 3.4 5.4 2.3 virginica 6.588
#> 150: 5.9 3.0 5.1 1.8 virginica 6.588
#> WSepal.Length
#> <num>
#> 1: 0.094
#> 2: -0.106
#> 3: -0.306
#> 4: -0.406
#> 5: -0.006
#> ---
#> 146: 0.112
#> 147: -0.288
#> 148: -0.088
#> 149: -0.388
#> 150: -0.688
str(d)
#> Classes ‘data.table’ and 'data.frame': 150 obs. of 7 variables:
#> $ Sepal.Length : num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#> $ Petal.Length : num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#> $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#> $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#> $ BSepal.Length: num 5.01 5.01 5.01 5.01 5.01 ...
#> $ WSepal.Length: num 0.094 -0.106 -0.306 -0.406 -0.006 ...
#> - attr(*, ".internal.selfref")=<externalptr>
rm(d)