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Standardise a variable or scale it to a percentage

Source: R/std.R
std.Rd

Vector helpers for dplyr::mutate(), following Stata's egen:

  • std(): Standardise to mean 0 and standard deviation 1, like egen z = std(x). Unlike scale(), it returns a plain vector.

  • pc() (pct()): Express each value as a percentage of the total, like egen p = pc(x), or as a proportion with prop = TRUE.

Usage

std(x, mean = 0, sd = 1)

pc(x, prop = FALSE)

pct(x, prop = FALSE)

Arguments

x

A numeric or logical vector. Labelled numeric vectors are used through their codes.

mean, sd

The mean and standard deviation of the result, like Stata's egen std(x), mean() std() options.

prop

If TRUE, pc() returns proportions (summing to 1) instead of percentages (summing to 100). Defaults to FALSE.

Value

A double vector the same length as x. Missing values stay missing. std() returns all NA when the standard deviation is zero or undefined (fewer than two observed values), and pc() when the total is zero or infinite, as Stata gives missing values there.

Details

The gt package also exports a pct() (for column widths), so prefer pc() when gt is attached. In grouped dplyr::mutate() (or with .by), the mean, standard deviation and total come from each group, like Stata's by g: egen.

See also

Other variable generation functions: as_dummy(), cut, panel, row_egen

Examples

std(c(1, 2, 3, NA))
#> [1] -1  0  1 NA

pc(c(2, 3, 5))
#> [1] 20 30 50

pc(c(2, 3, 5), prop = TRUE)
#> [1] 0.2 0.3 0.5

lifeexp |>
  dplyr::mutate(
    z = std(lexp),
    share = pc(popgrowth),
    .by = region
  )
#> # A tibble: 68 x 8
#>    region               country    popgrowth  lexp gnppc safewater      z  share
#>    <dbl+lbl>            <chr>          <dbl> <dbl> <dbl>     <dbl>  <dbl>  <dbl>
#>  1 1 [Europe & C. Asia] Albania         -0.6    74   870        49  0.303 -19.4 
#>  2 1 [Europe & C. Asia] Armenia         -1.2    70   570        83 -0.505 -38.7 
#>  3 1 [Europe & C. Asia] Austria          0.1    78 27810        97  1.11    3.23
#>  4 1 [Europe & C. Asia] Azerbaijan       0.9    64   510        49 -1.72   29.0 
#>  5 1 [Europe & C. Asia] Belarus         -0.5    68  1540        82 -0.909 -16.1 
#>  6 1 [Europe & C. Asia] Belgium          0.2    77 26530       100  0.909   6.45
#>  7 1 [Europe & C. Asia] Bosnia an~       1.8    74  1230        87  0.303  58.1 
#>  8 1 [Europe & C. Asia] Bulgaria        -0.7    71  1440        90 -0.303 -22.6 
#>  9 1 [Europe & C. Asia] Croatia         -0.1    72    NA        85 -0.101  -3.23
#> 10 1 [Europe & C. Asia] Czechia         -0.1    75  6140        95  0.505  -3.23
#> # i 58 more rows