standardize_variable() standardizes the selected columns in a data.frame using base::scale(). By default, this function overwrites the column to be scaled. Use the suffix argument to avoid this behavior.

standardize_variable() and standardise_variable() are synonyms.

standardize_variable(data, cols = dplyr::everything(), suffix = NULL)

standardise_variable(data, cols = dplyr::everything(), suffix = NULL)

Arguments

data

A data frame containing the variables to standardize.

cols

<tidy-select> Columns to standardize. Defaults to dplyr::everything().

suffix

A character suffix to be added to the scaled variables names. When suffix is set toNULL, the standardize_variable() function will overwrite the scaled variables. Defaults to NULL.

Value

A data frame with the standardized columns.

standardize_variable and grouped_df

Note that standardize_variable ignores grouping. Meaning that if you call this function on a grouped data frame (see dplyr::grouped_df), the overall variables' mean and standard deviation will be used for the standardization.

Examples

ho_et_al %>% standardize_variable(sdo)
#> # A tibble: 824 × 5 #> id condition sdo linkedfate hypodescent #> <chr> <chr> <dbl> <dbl> <dbl> #> 1 2 Low discrimination -0.470 6 2.33 #> 2 3 High discrimination -0.707 5.88 6 #> 3 4 High discrimination -0.529 6.62 6 #> 4 5 Low discrimination 1.84 5.12 5.67 #> 5 6 Low discrimination -0.351 4.38 4 #> 6 9 High discrimination 0.538 3.75 4 #> 7 11 High discrimination -1.12 6.62 5.33 #> 8 12 Low discrimination 1.84 4.62 4 #> 9 14 Low discrimination -1.06 5.12 3.67 #> 10 16 High discrimination -1.00 6.75 4 #> # … with 814 more rows
ho_et_al %>% standardize_variable(c(sdo, linkedfate), suffix = "scaled")
#> # A tibble: 824 × 7 #> id condition sdo linkedfate hypodescent sdo_scaled linkedfate_scal… #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 2 Low discrimination 1.81 6 2.33 -0.470 0.636 #> 2 3 High discrimination 1.56 5.88 6 -0.707 0.538 #> 3 4 High discrimination 1.75 6.62 6 -0.529 1.13 #> 4 5 Low discrimination 4.25 5.12 5.67 1.84 -0.0525 #> 5 6 Low discrimination 1.94 4.38 4 -0.351 -0.643 #> 6 9 High discrimination 2.88 3.75 4 0.538 -1.13 #> 7 11 High discrimination 1.12 6.62 5.33 -1.12 1.13 #> 8 12 Low discrimination 4.25 4.62 4 1.84 -0.446 #> 9 14 Low discrimination 1.19 5.12 3.67 -1.06 -0.0525 #> 10 16 High discrimination 1.25 6.75 4 -1.00 1.23 #> # … with 814 more rows