Assigns new masked names to selected variables in a data frame. All selected variables are combined into a single set and renamed with a common prefix. To mask different variable groups with different prefixes, call the function separately for each group.
Arguments
- data
A data frame.
- ...
Columns to mask. All arguments are combined into a single set. Each can be: Bare column names (e.g.,
var1, var2)A tidyselect expression (e.g.,
starts_with("treatment_"))A character vector of column names (e.g.,
c("var1", "var2"))
- prefix
character string to use as prefix for masked names. This becomes the base prefix, with numeric suffixes appended (e.g.,
prefix = "treatment_"produces "treatment_01", "treatment_02", etc.). The prefix is used as-is, so include a separator (e.g., underscore) if desired.
See also
mask_labels for masking values in a vector,
mask_variables for masking values in multiple variables, and
mask_variables_rowwise for rowwise value masking.
Examples
df <- data.frame(
treat_1 = c(1, 2, 3),
treat_2 = c(4, 5, 6),
outcome_a = c(7, 8, 9),
outcome_b = c(10, 11, 12),
id = 1:3
)
# Mask one set of variables
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
mask_names(df, starts_with("treat_"), prefix = "A_")
#> A_01 A_02 outcome_a outcome_b id
#> 1 1 4 7 10 1
#> 2 2 5 8 11 2
#> 3 3 6 9 12 3
# Using character vectors
mask_names(df, c("treat_1", "treat_2"), prefix = "A_")
#> A_02 A_01 outcome_a outcome_b id
#> 1 1 4 7 10 1
#> 2 2 5 8 11 2
#> 3 3 6 9 12 3
# Mask multiple sets separately
# Note that the order of masking matters
# Try to mix up the order of prefixes
# for different sets to ensure proper masking.
df |>
mask_names(starts_with("treat_"), prefix = "B_") |>
mask_names(starts_with("outcome_"), prefix = "A_")
#> B_01 B_02 A_02 A_01 id
#> 1 1 4 7 10 1
#> 2 2 5 8 11 2
#> 3 3 6 9 12 3
# Example with the 'williams' dataset
data(williams)
set.seed(42)
williams |>
mask_names(starts_with("SexUnres"), prefix = "A_") |>
mask_names(starts_with("Impul"), prefix = "B_") |>
colnames()
#> [1] "subject" "A_01" "A_05"
#> [4] "A_04" "A_03" "A_02"
#> [7] "B_02" "B_03" "B_01"
#> [10] "Opport_1" "Opport_2" "Opport_3"
#> [13] "Opport_4" "Opport_5" "Opport_6_r"
#> [16] "InvEdu_1_r" "InvEdu_2_r" "InvChild_1"
#> [19] "InvChild_2_r" "age" "gender"
#> [22] "ecology" "duration_in_seconds" "attention_1"
#> [25] "attention_2"